The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

A Study of Accomodation of Prosodic and Temporal Features in Spoken Dialogues in View of Speech Technology Applications

Inter-speaker accommodation is a well-known property of human speech and human interaction in general. Broadly it refers to the behavioural patterns of two (or more) interactants and the effect of the (verbal and non-verbal) behaviour of each to that of the other(s). Implementation of thisbehavior in spoken dialogue systems is desirable as an improvement on the naturalness of humanmachine interaction. However, traditional qualitative descriptions of accommodation phenomena do not provide sufficient information for such an implementation. Therefore, a quantitativedescription of inter-speaker accommodation is required. This thesis proposes a methodology of monitoring accommodation during a human or humancomputer dialogue, which utilizes a moving average filter over sequential frames for each speaker. These frames are time-aligned across the speakers, hence the name Time Aligned Moving Average (TAMA). Analysis of spontaneous human dialogue recordings by means of the TAMA methodology reveals ubiquitous accommodation of prosodic features (pitch, intensity and speech rate) across interlocutors, and allows for statistical (time series) modeling of the behaviour, in a way which is meaningful for implementation in spoken dialogue system (SDS) environments.In addition, a novel dialogue representation is proposed that provides an additional point of view to that of TAMA in monitoring accommodation of temporal features (inter-speaker pause length and overlap frequency). This representation is a percentage turn distribution of individual speakercontributions in a dialogue frame which circumvents strict attribution of speaker-turns, by considering both interlocutors as synchronously active. Both TAMA and turn distribution metrics indicate that correlation of average pause length and overlap frequency between speakers can be attributed to accommodation (a debated issue), and point to possible improvements in SDS “turntaking” behaviour. Although the findings of the prosodic and temporal analyses can directly inform SDS implementations, further work is required in order to describe inter-speaker accommodation sufficiently, as well as to develop an adequate testing platform for evaluating the magnitude ofperceived improvement in human-machine interaction. Therefore, this thesis constitutes a first step towards a convincingly useful implementation of accommodation in spoken dialogue systems

The analysis of breathing and rhythm in speech

Speech rhythm can be described as the temporal patterning by which speech events, such as vocalic onsets, occur. Despite efforts to quantify and model speech rhythm across languages, it remains a scientifically enigmatic aspect of prosody. For instance, one challenge lies in determining how to best quantify and analyse speech rhythm. Techniques range from manual phonetic annotation to the automatic extraction of acoustic features. It is currently unclear how closely these differing approaches correspond to one another. Moreover, the primary means of speech rhythm research has been the analysis of the acoustic signal only. Investigations of speech rhythm may instead benefit from a range of complementary measures, including physiological recordings, such as of respiratory effort. This thesis therefore combines acoustic recording with inductive plethysmography (breath belts) to capture temporal characteristics of speech and speech breathing rhythms. The first part examines the performance of existing phonetic and algorithmic techniques for acoustic prosodic analysis in a new corpus of rhythmically diverse English and Mandarin speech. The second part addresses the need for an automatic speech breathing annotation technique by developing a novel function that is robust to the noisy plethysmography typical of spontaneous, naturalistic speech production. These methods are then applied in the following section to the analysis of English speech and speech breathing in a second, larger corpus. Finally, behavioural experiments were conducted to investigate listeners' perception of speech breathing using a novel gap detection task. The thesis establishes the feasibility, as well as limits, of automatic methods in comparison to manual annotation. In the speech breathing corpus analysis, they help show that speakers maintain a normative, yet contextually adaptive breathing style during speech. The perception experiments in turn demonstrate that listeners are sensitive to the violation of these speech breathing norms, even if unconsciously so. The thesis concludes by underscoring breathing as a necessary, yet often overlooked, component in speech rhythm planning and production

Holistic Vocabulary Independent Spoken Term Detection

Within this thesis, we aim at designing a loosely coupled holistic system for Spoken Term Detection (STD) on heterogeneous German broadcast data in selected application scenarios. Starting from STD on the 1-best output of a word-based speech recognizer, we study the performance of several subword units for vocabulary independent STD on a linguistically and acoustically challenging German corpus. We explore the typical error sources in subword STD, and find that they differ from the error sources in word-based speech search. We select, extend and combine a set of state-of-the-art methods for error compensation in STD in order to explicitly merge the corresponding STD error spaces through anchor-based approximate lattice retrieval. Novel methods for STD result verification are proposed in order to increase retrieval precision by exploiting external knowledge at search time. Error-compensating methods for STD typically suffer from high response times on large scale databases, and we propose scalable approaches suitable for large corpora. Highest STD accuracy is obtained by combining anchor-based approximate retrieval from both syllable lattice ASR and syllabified word ASR into a hybrid STD system, and pruning the result list using external knowledge with hybrid contextual and anti-query verification.Die vorliegende Arbeit beschreibt ein lose gekoppeltes, ganzheitliches System zur Sprachsuche auf heterogenenen deutschen Sprachdaten in unterschiedlichen Anwendungsszenarien. Ausgehend von einer wortbasierten Sprachsuche auf dem Transkript eines aktuellen Wort-Erkenners werden zunächst unterschiedliche Subwort-Einheiten für die vokabularunabhängige Sprachsuche auf deutschen Daten untersucht. Auf dieser Basis werden die typischen Fehlerquellen in der Subwort-basierten Sprachsuche analysiert. Diese Fehlerquellen unterscheiden sich vom Fall der klassichen Suche im Worttranskript und müssen explizit adressiert werden. Die explizite Kompensation der unterschiedlichen Fehlerquellen erfolgt durch einen neuartigen hybriden Ansatz zur effizienten Ankerbasierten unscharfen Wortgraph-Suche. Darüber hinaus werden neuartige Methoden zur Verifikation von Suchergebnissen vorgestellt, die zur Suchzeit verfügbares externes Wissen einbeziehen. Alle vorgestellten Verfahren werden auf einem umfangreichen Satz von deutschen Fernsehdaten mit Fokus auf ausgewählte, repräsentative Einsatzszenarien evaluiert. Da Methoden zur Fehlerkompensation in der Sprachsuchforschung typischerweise zu hohen Laufzeiten bei der Suche in großen Archiven führen, werden insbesondere auch Szenarien mit sehr großen Datenmengen betrachtet. Die höchste Suchleistung für Archive mittlerer Größe wird durch eine unscharfe und Anker-basierte Suche auf einem hybriden Index aus Silben-Wortgraphen und silbifizierter Wort-Erkennung erreicht, bei der die Suchergebnisse mit hybrider Verifikation bereinigt werden

On the voice-activated question answering

[EN] Question answering (QA) is probably one of the most challenging tasks in the field of natural language processing. It requires search engines that are capable of extracting concise, precise fragments of text that contain an answer to a question posed by the user. The incorporation of voice interfaces to the QA systems adds a more natural and very appealing perspective for these systems. This paper provides a comprehensive description of current state-of-the-art voice-activated QA systems. Finally, the scenarios that will emerge from the introduction of speech recognition in QA will be discussed. © 2006 IEEE.This work was supported in part by Research Projects TIN2009-13391-C04-03 and TIN2008-06856-C05-02. This paper was recommended by Associate Editor V. Marik.Rosso, P.; Hurtado Oliver, LF.; Segarra Soriano, E.; Sanchís Arnal, E. (2012). On the voice-activated question answering. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews. 42(1):75-85. https://doi.org/10.1109/TSMCC.2010.2089620S758542

The contribution of voice quality to the expression of politeness: an experimental study

This thesis investigates the role of voice quality in the expression of politeness under con¬ ditions of varying relative social status among Japanese male speakers. The thesis also sheds light on four important methodological issues: 1) experimental control of sociolinguistic aspects, 2) eliciting semi-natural spontaneous speech which satisfies naturalness, 3) recording quality suitable for voice quality analysis, and 4) the use of direct waveform and spectrum measurement as a non-invasive method for measuring glottal characteristics related to perceived voice quality.Japanese has been believed to rely on what has been called "negative politeness" (formality and deference). Since explicitly expressing deference under the Keigo (Japanese system of honorifics) requires mastery of a highly complex system, in daily conversation, this function may be taken over by vocal paralinguistics. Also, as the Keigo system is not supposed to convey "positive politeness" (friendliness and solidarity), vocal paralinguis¬ tics may contribute to this aspect of politeness. The use of high fundamental frequency (FO), which has been considered a universal cue of politeness, is more associated with femininity in Japanese, and this usage of FO is not observed in male speakers, who possibly employ other vocal cues to express politeness. Therefore this study focuses on voice quality of male speakers in expressing politeness.To obtain natural, unscripted utterances, the speech data were collected with the Map Task. This task also allows us to study the effect of manipulating relative social status differences among participants in the same community. For voice quality analysis, direct waveform and spectrum measurement (Hanson 1995) was employed. We mainly computed relative amplitudes of harmonics and formant peaks in the spectrum, as alternatives to certain well known parameters used in previous studies. We also measured FO and amplitude perturbations as possible indicators of voice quality.An experiment was conducted to observe the alignment between acoustic measures and the perceived politeness from both written and spoken versions of the utterances obtained from the Map Task. The results suggest two principal findings. First, Keigo does not play a role in conveying politeness in everyday conversation, but speakers showed politeness through voice quality variations. Second, in judging the politeness of test utterances, listeners reacted to the irregularity of the waveform and spectral characteristics in the third formant region. In particular, the speakers' spectral tilt range and correlation coefficient between ratings of politeness and spectral tilt are anti-proportional, and extremely large or small spectral tilt values were consistently perceived as not appropriate when addressing social superiors. These results are expected to contribute to both sociolinguistics and speech technology, such as speech synthesis

Temporal entrainment in overlapping speech

Wlodarczak M. Temporal entrainment in overlapping speech. Bielefeld: Bielefeld University; 2014

Vocal accommodation in human-computer interaction : modeling and integration into spoken dialogue systems

With the rapidly increasing usage of voice-activated devices worldwide, verbal communication with computers is steadily becoming more common. Although speech is the principal natural manner of human communication, it is still challenging for computers, and users had been growing accustomed to adjusting their speaking style for computers. Such adjustments occur naturally, and typically unconsciously, in humans during an exchange to control the social distance between the interlocutors and improve the conversation’s efficiency. This phenomenon is called accommodation and it occurs on various modalities in human communication, like hand gestures, facial expressions, eye gaze, lexical and grammatical choices, and others. Vocal accommodation deals with phonetic-level changes occurring in segmental and suprasegmental features. A decrease in the difference between the speakers’ feature realizations results in convergence, while an increasing distance leads to divergence. The lack of such mutual adjustments made naturally by humans in computers’ speech creates a gap between human-human and human-computer interactions. Moreover, voice-activated systems currently speak in exactly the same manner to all users, regardless of their speech characteristics or realizations of specific features. Detecting phonetic variations and generating adaptive speech output would enhance user personalization, offer more human-like communication, and ultimately should improve the overall interaction experience. Thus, investigating these aspects of accommodation will help to understand and improving human-computer interaction. This thesis provides a comprehensive overview of the required building blocks for a roadmap toward the integration of accommodation capabilities into spoken dialogue systems. These include conducting human-human and human-computer interaction experiments to examine the differences in vocal behaviors, approaches for modeling these empirical findings, methods for introducing phonetic variations in synthesized speech, and a way to combine all these components into an accommodative system. While each component is a wide research field by itself, they depend on each other and hence should be jointly considered. The overarching goal of this thesis is therefore not only to show how each of the aspects can be further developed, but also to demonstrate and motivate the connections between them. A special emphasis is put throughout the thesis on the importance of the temporal aspect of accommodation. Humans constantly change their speech over the course of a conversation. Therefore, accommodation processes should be treated as continuous, dynamic phenomena. Measuring differences in a few discrete points, e.g., beginning and end of an interaction, may leave many accommodation events undiscovered or overly smoothed. To justify the effort of introducing accommodation in computers, it should first be proven that humans even show any phonetic adjustments when talking to a computer as they do with a human being. As there is no definitive metric for measuring accommodation and evaluating its quality, it is important to empirically study humans productions to later use as references for possible behaviors. In this work, this investigation encapsulates different experimental configurations to achieve a better picture of accommodation effects. First, vocal accommodation was inspected where it naturally occurs, namely in spontaneous human-human conversations. For this purpose, a collection of real-world sales conversations, each with a different representative-prospect pair, was collected and analyzed. These conversations offer a glance into accommodation effects in authentic, unscripted interactions with the common goal of negotiating a deal on the one hand, but with the individual facet of each side of trying to get the best terms on the other hand. The conversations were analyzed using cross-correlation and time series techniques to capture the change dynamics over time. It was found that successful conversations are distinguishable from failed ones by multiple measures. Furthermore, the sales representative proved to be better at leading the vocal changes, i.e., making the prospect follow their speech styles rather than the other way around. They also showed a stronger tendency to take that lead at an earlier stage, all the more so in successful conversations. The fact that accommodation occurs more by trained speakers and improves their performances fits anecdotal best practices of sales experts, which are now also proven scientifically. Following these results, the next experiment came closer to the final goal of this work and investigated vocal accommodation effects in human-computer interaction. This was done via a shadowing experiment, which offers a controlled setting for examining phonetic variations. As spoken dialogue systems with such accommodation capabilities (like this work aims to achieve) do not exist yet, a simulated system was used to introduce these changes to the participants, who believed they help with the testing of a language learning tutoring system. After determining their preference concerning three segmental phonetic features, participants were listen-ing to either natural or synthesized voices of male and female speakers, which produced the participants’ dispreferred variation of the aforementioned features. Accommodation occurred in all cases, but the natural voices triggered stronger effects. Nevertheless, it can be concluded that participants were accommodating toward synthetic voices as well, which means that social mechanisms are applied in humans also when speaking with computer-based interlocutors. The shadowing paradigm was utilized also to test whether accommodation is a phenomenon associated only with speech or with other vocal productions as well. To that end, accommodation in the singing of familiar and novel music was examined. Interestingly, accommodation was found in both cases, though in different ways. While participants seemed to use the familiar piece merely as a reference for singing more accurately, the novel piece became the goal for complete replicate. For example, one difference was that mostly pitch corrections were introduced in the former case, while in the latter also key and rhythmic patterns were adopted. Some of those findings were expected and they show that people’s more salient features are also harder to modify using external auditory influence. Lastly, a multiparty experiment with spontaneous human-human-computer interactions was carried out to compare accommodation in human-directed and computer-directed speech. The participants solved tasks for which they needed to talk both with a confederate and with an agent. This allows a direct comparison of their speech based on the addressee within the same conversation, which has not been done so far. Results show that some participants’ vocal behavior changed similarly when talking to the confederate and the agent, while others’ speech varied only with the confederate. Further analysis found that the greatest factor for this difference was the order in which the participants talked with the interlocutors. Apparently, those who first talked to the agent alone saw it more as a social actor in the conversation, while those who interacted with it after talking to the confederate treated it more as a means to achieve a goal, and thus behaved differently with it. In the latter case, the variations in the human-directed speech were much more prominent. Differences were also found between the analyzed features, but the task type did not influence the degree of accommodation effects. The results of these experiments lead to the conclusion that vocal accommodation does occur in human-computer interactions, even if often to lesser degrees. With the question of whether people accommodate to computer-based interlocutors as well answered, the next step would be to describe accommodative behaviors in a computer-processable manner. Two approaches are proposed here: computational and statistical. The computational model aims to capture the presumed cognitive process associated with accommodation in humans. This comprises various steps, such as detecting the variable feature’s sound, adding instances of it to the feature’s mental memory, and determining how much the sound will change while taking into account both its current representation and the external input. Due to its sequential nature, this model was implemented as a pipeline. Each of the pipeline’s five steps corresponds to a specific part of the cognitive process and can have one or more parameters to control its output (e.g., the size of the feature’s memory or the accommodation pace). Using these parameters, precise accommodative behaviors can be crafted while applying expert knowledge to motivate the chosen parameter values. These advantages make this approach suitable for experimentation with pre-defined, deterministic behaviors where each step can be changed individually. Ultimately, this approach makes a system vocally responsive to users’ speech input. The second approach grants more evolved behaviors, by defining different core behaviors and adding non-deterministic variations on top of them. This resembles human behavioral patterns, as each person has a base way of accommodating (or not accommodating), which may arbitrarily change based on the specific circumstances. This approach offers a data-driven statistical way to extract accommodation behaviors from a given collection of interactions. First, the target feature’s values of each speaker in an interaction are converted into continuous interpolated lines by drawing one sample from the posterior distribution of a Gaussian process conditioned on the given values. Then, the gradients of these lines, which represent rates of mutual change, are used to defined discrete levels of change based on their distribution. Finally, each level is assigned a symbol, which ultimately creates a symbol sequence representation for each interaction. The sequences are clustered so that each cluster stands for a type of behavior. The sequences of a cluster can then be used to calculate n-gram probabilities that enable the generation of new sequences of the captured behavior. The specific output value is sampled from the range corresponding to the generated symbol. With this approach, accommodation behaviors are extracted directly from data, as opposed to manually crafting them. However, it is harder to describe what exactly these behaviors represent and motivate the use of one of them over the other. To bridge this gap between these two approaches, it is also discussed how they can be combined to benefit from the advantages of both. Furthermore, to generate more structured behaviors, a hierarchy of accommodation complexity levels is suggested here, from a direct adoption of users’ realizations, via specified responsiveness, and up to independent core behaviors with non-deterministic variational productions. Besides a way to track and represent vocal changes, an accommodative system also needs a text-to-speech component that is able to realize those changes in the system’s speech output. Speech synthesis models are typically trained once on data with certain characteristics and do not change afterward. This prevents such models from introducing any variation in specific sounds and other phonetic features. Two methods for directly modifying such features are explored here. The first is based on signal modifications applied to the output signal after it was generated by the system. The processing is done between the timestamps of the target features and uses pre-defined scripts that modify the signal to achieve the desired values. This method is more suitable for continuous features like vowel quality, especially in the case of subtle changes that do not necessarily lead to a categorical sound change. The second method aims to capture phonetic variations in the training data. To that end, a training corpus with phonemic representations is used, as opposed to the regular graphemic representations. This way, the model can learn more direct relations between phonemes and sound instead of surface forms and sound, which, depending on the language, might be more complex and depend on their surrounding letters. The target variations themselves don’t necessarily need to be explicitly present in the training data, all time the different sounds are naturally distinguishable. In generation time, the current target feature’s state determines the phoneme to use for generating the desired sound. This method is suitable for categorical changes, especially for contrasts that naturally exist in the language. While both methods have certain limitations, they provide a proof of concept for the idea that spoken dialogue systems may phonetically adapt their speech output in real-time and without re-training their text-to-speech models. To combine the behavior definitions and the speech manipulations, a system is required, which can connect these elements to create a complete accommodation capability. The architecture suggested here extends the standard spoken dialogue system with an additional module, which receives the transcribed speech signal from the speech recognition component without influencing the input to the language understanding component. While language the understanding component uses only textual transcription to determine the user’s intention, the added component process the raw signal along with its phonetic transcription. In this extended architecture, the accommodation model is activated in the added module and the information required for speech manipulation is sent to the text-to-speech component. However, the text-to-speech component now has two inputs, viz. the content of the system’s response coming from the language generation component and the states of the defined target features from the added component. An implementation of a web-based system with this architecture is introduced here, and its functionality is showcased by demonstrating how it can be used to conduct a shadowing experiment automatically. This has two main advantage: First, since the system recognizes the participants’ phonetic variations and automatically selects the appropriate variation to use in its response, the experimenter saves time and prevents manual annotation errors. The experimenter also automatically gains additional information, like exact timestamps of utterances, real-time visualization of the interlocutors’ productions, and the possibility to replay and analyze the interaction after the experiment is finished. The second advantage is scalability. Multiple instances of the system can run on a server and be accessed by multiple clients at the same time. This not only saves time and the logistics of bringing participants into a lab, but also allows running the experiment with different configurations (e.g., other parameter values or target features) in a controlled and reproducible way. This completes a full cycle from examining human behaviors to integrating accommodation capabilities. Though each part of it can undoubtedly be further investigated, the emphasis here is on how they depend and connect to each other. Measuring changes features without showing how they can be modeled or achieving flexible speech synthesis without considering the desired final output might not lead to the final goal of introducing accommodation capabilities into computers. Treating accommodation in human-computer interaction as one large process rather than isolated sub-problems lays the ground for more comprehensive and complete solutions in the future.Heutzutage wird die verbale Interaktion mit Computern immer gebräuchlicher, was der rasant wachsenden Anzahl von sprachaktivierten Geräten weltweit geschuldet ist. Allerdings stellt die computerseitige Handhabung gesprochener Sprache weiterhin eine große Herausforderung dar, obwohl sie die bevorzugte Art zwischenmenschlicher Kommunikation repräsentiert. Dieser Umstand führt auch dazu, dass Benutzer ihren Sprachstil an das jeweilige Gerät anpassen, um diese Handhabung zu erleichtern. Solche Anpassungen kommen in menschlicher gesprochener Sprache auch in der zwischenmenschlichen Kommunikation vor. Üblicherweise ereignen sie sich unbewusst und auf natürliche Weise während eines Gesprächs, etwa um die soziale Distanz zwischen den Gesprächsteilnehmern zu kontrollieren oder um die Effizienz des Gesprächs zu verbessern. Dieses Phänomen wird als Akkommodation bezeichnet und findet auf verschiedene Weise während menschlicher Kommunikation statt. Sie äußert sich zum Beispiel in der Gestik, Mimik, Blickrichtung oder aber auch in der Wortwahl und dem verwendeten Satzbau. Vokal- Akkommodation beschäftigt sich mit derartigen Anpassungen auf phonetischer Ebene, die sich in segmentalen und suprasegmentalen Merkmalen zeigen. Werden Ausprägungen dieser Merkmale bei den Gesprächsteilnehmern im Laufe des Gesprächs ähnlicher, spricht man von Konvergenz, vergrößern sich allerdings die Unterschiede, so wird dies als Divergenz bezeichnet. Dieser natürliche gegenseitige Anpassungsvorgang fehlt jedoch auf der Seite des Computers, was zu einer Lücke in der Mensch-Maschine-Interaktion führt. Darüber hinaus verwenden sprachaktivierte Systeme immer dieselbe Sprachausgabe und ignorieren folglich etwaige Unterschiede zum Sprachstil des momentanen Benutzers. Die Erkennung dieser phonetischen Abweichungen und die Erstellung von anpassungsfähiger Sprachausgabe würden zur Personalisierung dieser Systeme beitragen und könnten letztendlich die insgesamte Benutzererfahrung verbessern. Aus diesem Grund kann die Erforschung dieser Aspekte von Akkommodation helfen, Mensch-Maschine-Interaktion besser zu verstehen und weiterzuentwickeln. Die vorliegende Dissertation stellt einen umfassenden Überblick zu Bausteinen bereit, die nötig sind, um Akkommodationsfähigkeiten in Sprachdialogsysteme zu integrieren. In diesem Zusammenhang wurden auch interaktive Mensch-Mensch- und Mensch- Maschine-Experimente durchgeführt. In diesen Experimenten wurden Differenzen der vokalen Verhaltensweisen untersucht und Methoden erforscht, wie phonetische Abweichungen in synthetische Sprachausgabe integriert werden können. Um die erhaltenen Ergebnisse empirisch auswerten zu können, wurden hierbei auch verschiedene Modellierungsansätze erforscht. Fernerhin wurde der Frage nachgegangen, wie sich die betreffenden Komponenten kombinieren lassen, um ein Akkommodationssystem zu konstruieren. Jeder dieser Aspekte stellt für sich genommen bereits einen überaus breiten Forschungsbereich dar. Allerdings sind sie voneinander abhängig und sollten zusammen betrachtet werden. Aus diesem Grund liegt ein übergreifender Schwerpunkt dieser Dissertation darauf, nicht nur aufzuzeigen, wie sich diese Aspekte weiterentwickeln lassen, sondern auch zu motivieren, wie sie zusammenhängen. Ein weiterer Schwerpunkt dieser Arbeit befasst sich mit der zeitlichen Komponente des Akkommodationsprozesses, was auf der Beobachtung fußt, dass Menschen im Laufe eines Gesprächs ständig ihren Sprachstil ändern. Diese Beobachtung legt nahe, derartige Prozesse als kontinuierliche und dynamische Prozesse anzusehen. Fasst man jedoch diesen Prozess als diskret auf und betrachtet z.B. nur den Beginn und das Ende einer Interaktion, kann dies dazu führen, dass viele Akkommodationsereignisse unentdeckt bleiben oder übermäßig geglättet werden. Um die Entwicklung eines vokalen Akkommodationssystems zu rechtfertigen, muss zuerst bewiesen werden, dass Menschen bei der vokalen Interaktion mit einem Computer ein ähnliches Anpassungsverhalten zeigen wie bei der Interaktion mit einem Menschen. Da es keine eindeutig festgelegte Metrik für das Messen des Akkommodationsgrades und für die Evaluierung der Akkommodationsqualität gibt, ist es besonders wichtig, die Sprachproduktion von Menschen empirisch zu untersuchen, um sie als Referenz für mögliche Verhaltensweisen anzuwenden. In dieser Arbeit schließt diese Untersuchung verschiedene experimentelle Anordnungen ein, um einen besseren Überblick über Akkommodationseffekte zu erhalten. In einer ersten Studie wurde die vokale Akkommodation in einer Umgebung untersucht, in der sie natürlich vorkommt: in einem spontanen Mensch-Mensch Gespräch. Zu diesem Zweck wurde eine Sammlung von echten Verkaufsgesprächen gesammelt und analysiert, wobei in jedem dieser Gespräche ein anderes Handelsvertreter-Neukunde Paar teilgenommen hatte. Diese Gespräche verschaffen einen Einblick in Akkommodationseffekte während spontanen authentischen Interaktionen, wobei die Gesprächsteilnehmer zwei Ziele verfolgen: zum einen soll ein Geschäft verhandelt werden, zum anderen möchte aber jeder Teilnehmer für sich die besten Bedingungen aushandeln. Die Konversationen wurde durch das Kreuzkorrelation-Zeitreihen-Verfahren analysiert, um die dynamischen Änderungen im Zeitverlauf zu erfassen. Hierbei kam zum Vorschein, dass sich erfolgreiche Konversationen von fehlgeschlagenen Gesprächen deutlich unterscheiden lassen. Überdies wurde festgestellt, dass die Handelsvertreter die treibende Kraft von vokalen Änderungen sind, d.h. sie können die Neukunden eher dazu zu bringen, ihren Sprachstil anzupassen, als andersherum. Es wurde auch beobachtet, dass sie diese Akkommodation oft schon zu einem frühen Zeitpunkt auslösen, was besonders bei erfolgreichen Gesprächen beobachtet werden konnte. Dass diese Akkommodation stärker bei trainierten Sprechern ausgelöst wird, deckt sich mit den meist anekdotischen Empfehlungen von erfahrenen Handelsvertretern, die bisher nie wissenschaftlich nachgewiesen worden sind. Basierend auf diesen Ergebnissen beschäfti

Proceedings of the LREC 2018 Special Speech Sessions

LREC 2018 Special Speech Sessions "Speech Resources Collection in Real-World Situations"; Phoenix Seagaia Conference Center, Miyazaki; 2018-05-0