Alcohol Language Corpus

The Alcohol Language Corpus (ALC) is the first publicly available speech corpus comprising intoxicated and sober speech of 162 female and male German speakers. Recordings are done in the automotive environment to allow for the development of automatic alcohol detection and to ensure a consistent acoustic environment for the alcoholized and the sober recording. The recorded speech covers a variety of contents and speech styles. Breath and blood alcohol concentration measurements are provided for all speakers. A transcription according to SpeechDat/Verbmobil standards and disfluency tagging as well as an automatic phonetic segmentation are part of the corpus. An Emu version of ALC allows easy access to basic speech parameters as well as the us of R for statistical analysis of selected parts of ALC. ALC is available without restriction for scientific or commercial use at the Bavarian Archive for Speech Signals

An exploration of the rhythm of Malay

In recent years there has been a surge of interest in speech rhythm. However we still lack a clear understanding of the nature of rhythm and rhythmic differences across languages. Various metrics have been proposed as means for measuring rhythm on the phonetic level and making typological comparisons between languages (Ramus et al, 1999; Grabe & Low, 2002; Dellwo, 2006) but the debate is ongoing on the extent to which these metrics capture the rhythmic basis of speech (Arvaniti, 2009; Fletcher, in press). Furthermore, cross linguistic studies of rhythm have covered a relatively small number of languages and research on previously unclassified languages is necessary to fully develop the typology of rhythm. This study examines the rhythmic features of Malay, for which, to date, relatively little work has been carried out on aspects rhythm and timing. The material for the analysis comprised 10 sentences produced by 20 speakers of standard Malay (10 males and 10 females). The recordings were first analysed using rhythm metrics proposed by Ramus et. al (1999) and Grabe & Low (2002). These metrics (∆C, %V, rPVI, nPVI) are based on durational measurements of vocalic and consonantal intervals. The results indicated that Malay clustered with other so-called syllable-timed languages like French and Spanish on the basis of all metrics. However, underlying the overall findings for these metrics there was a large degree of variability in values across speakers and sentences, with some speakers having values in the range typical of stressed-timed languages like English. Further analysis has been carried out in light of Fletcher’s (in press) argument that measurements based on duration do not wholly reflect speech rhythm as there are many other factors that can influence values of consonantal and vocalic intervals, and Arvaniti’s (2009) suggestion that other features of speech should also be considered in description of rhythm to discover what contributes to listeners’ perception of regularity. Spectrographic analysis of the Malay recordings brought to light two parameters that displayed consistency and regularity for all speakers and sentences: the duration of individual vowels and the duration of intervals between intensity minima. This poster presents the results of these investigations and points to connections between the features which seem to be consistently regulated in the timing of Malay connected speech and aspects of Malay phonology. The results are discussed in light of current debate on the descriptions of rhythm

An acoustic-phonetic approach in automatic Arabic speech recognition

In a large vocabulary speech recognition system the broad phonetic classification technique is used instead of detailed phonetic analysis to overcome the variability in the acoustic realisation of utterances. The broad phonetic description of a word is used as a means of lexical access, where the lexicon is structured into sets of words sharing the same broad phonetic labelling. This approach has been applied to a large vocabulary isolated word Arabic speech recognition system. Statistical studies have been carried out on 10,000 Arabic words (converted to phonemic form) involving different combinations of broad phonetic classes. Some particular features of the Arabic language have been exploited. The results show that vowels represent about 43% of the total number of phonemes. They also show that about 38% of the words can uniquely be represented at this level by using eight broad phonetic classes. When introducing detailed vowel identification the percentage of uniquely specified words rises to 83%. These results suggest that a fully detailed phonetic analysis of the speech signal is perhaps unnecessary. In the adopted word recognition model, the consonants are classified into four broad phonetic classes, while the vowels are described by their phonemic form. A set of 100 words uttered by several speakers has been used to test the performance of the implemented approach. In the implemented recognition model, three procedures have been developed, namely voiced-unvoiced-silence segmentation, vowel detection and identification, and automatic spectral transition detection between phonemes within a word. The accuracy of both the V-UV-S and vowel recognition procedures is almost perfect. A broad phonetic segmentation procedure has been implemented, which exploits information from the above mentioned three procedures. Simple phonological constraints have been used to improve the accuracy of the segmentation process. The resultant sequence of labels are used for lexical access to retrieve the word or a small set of words sharing the same broad phonetic labelling. For the case of having more than one word-candidates, a verification procedure is used to choose the most likely one

A COMPREHENSIVE REVIEW OF INTONATION: PSYCHOACOUSTICS MODELING OF PROSODIC PROMINENCE

Bolinger (1978:475), one of the foremost authorities on prosody of a generation ago, said that “Intonation is a half-tamed savage. To understand the tamed or linguistically harnessed half of him, one has to make friends with the wild half.” This review provides a brief explanation for the tamed and untamed halves of intonation. It is argued here that the pitch-centered approach that has been used for several decades is responsible for why one half of intonation remains untamed. To tame intonation completely, a holistic acoustic approach is required that takes intensity and duration as seriously as it does pitch. Speech is a three-dimensional physical entity in which all three correlates work independently and interdependently. Consequently, a methodology that addresses intonation comprehensively is more likely to yield better results. Psychoacoustics seems to be well positioned for this task. Nearly 100 years of experimentations have led to the discoveries of Just Noticeable Difference (JNDs) thresholds that can be summoned to help tame intonation completely. The framework discussed here expands the analytical resources and facilitates an optimal description of intonation. It calculates and ranks the relative functional load (RFL) of pitch, intensity, and duration, and uses the results to compute the melodicity score of utterances. The findings replicate, based on JNDs, how the naked ear perceives intonation on a four-point Likert melodicity scale

Alcohol Language Corpus

The Alcohol Language Corpus (ALC) is the first publicly available speech corpus comprising intoxicated and sober speech of 162 female and male German speakers. Recordings are done in the automotive environment to allow for the development of automatic alcohol detection and to ensure a consistent acoustic environment for the alcoholized and the sober recording. The recorded speech covers a variety of contents and speech styles. Breath and blood alcohol concentration measurements are provided for all speakers. A transcription according to SpeechDat/Verbmobil standards and disfluency tagging as well as an automatic phonetic segmentation are part of the corpus. An Emu version of ALC allows easy access to basic speech parameters as well as the us of R for statistical analysis of selected parts of ALC. ALC is available without restriction for scientific or commercial use at the Bavarian Archive for Speech Signals

A Tutorial on Acoustic Phonetic Feature Extraction for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) Applications in African Languages

At present, Siri, Dragon Dictate, Google Voice, and Alexa-like functionalities are not available in any indigenous African language. Yet, a 2015 Pew Research found that between 2002 to 2014, mobile phone usage increased tenfold in Africa, from 8% to 83%.[1] The Acoustic Phonetic Approach (APA) discussed in this paper lays the foundation that will make Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) applications possible in African languages. The paper is written as a tutorial so that others can use the information therein to help digitalize many of the continent’s indigenous languages. [1] http://www.pewglobal.org/2015/04/15/cell-phones-in-africa-communication-lifeline/. Retrieved on November 10, 2017

A Comprehenisve Review of the Acoustic Correlate of Duration and Its Linguistic Implications

Speech is a three-dimensional physical entity that consists of F0/pitch, intensity, and duration. This paper is the last of three publications devoted to a comprehensive review of the aforementioned correlates. Koffi (2019) and Koffi (2020) focused on F0/Pitch and intensity respectively. The current study is devoted entirely to duration. The goal behind these comprehensive reviews is to assemble in a single paper as much information as possible so that speech data can be interpreted accurately in accordance with acoustic phonetics, engineering, and speech signal processing norms. With regard to duration, first, it must be noted that its measurements are to be interpreted linearly but not literally. Secondly, it is worth emphasizing that speech signals have their own intrinsic durational characteristics. Consequently, the duration of a syllable, a word, a phrase, or an utterance is the sum total of the intrinsic durations of its constitutive segments. Yet, the duration of speech signals is also conditioned by factors as diverse as articulatory gestures, the syntactic distribution of words, the venue where the speech event takes place, the relationship between the talker and the hearer, the formality or informality of the occasion, the tempo of delivery, among others. The key linguistic factors that affect duration are discussed in this paper. Though the examples are mostly from American English and Anyi (a Niger-Congo/Akan language spoken in Côte d’Ivoire) the insights derived from this paper apply broadly to other languages because the speech production and perception mechanisms that undergird duration are the same for every language

Segmental Durations of Speech

This dissertation considers the segmental durations of speech from the viewpoint of speech technology, especially speech synthesis. The idea is that better models of segmental durations lead to higher naturalness and better intelligibility. These features are the key factors for better usability and generality of synthesized speech technology. Even though the studies are based on a Finnish corpus the approaches apply to all other languages as well. This is possibly due to the fact that most of the studies included in this dissertation are about universal effects taking place on utterance boundaries. Also the methods invented and used here are suitable for any other study of another language. This study is based on two corpora of news reading speech and sentences read aloud. The other corpus is read aloud by a 39-year-old male, whilst the other consists of several speakers in various situations. The use of two corpora is twofold: it involves a comparison of the corpora and a broader view on the matters of interest. The dissertation begins with an overview to the phonemes and the quantity system in the Finnish language. Especially, we are covering the intrinsic durations of phonemes and phoneme categories, as well as the difference of duration between short and long phonemes. The phoneme categories are presented to facilitate the problem of variability of speech segments. In this dissertation we cover the boundary-adjacent effects on segmental durations. In initial positions of utterances we find that there seems to be initial shortening in Finnish, but the result depends on the level of detail and on the individual phoneme. On the phoneme level we find that the shortening or lengthening only affects the very first ones at the beginning of an utterance. However, on average, the effect seems to shorten the whole first word on the word level. We establish the effect of final lengthening in Finnish. The effect in Finnish has been an open question for a long time, whilst Finnish has been the last missing piece for it to be a universal phenomenon. Final lengthening is studied from various angles and it is also shown that it is not a mere effect of prominence or an effect of speech corpus with high inter- and intra-speaker variation. The effect of final lengthening seems to extend from the final to the penultimate word. On a phoneme level it reaches a much wider area than the initial effect. We also present a normalization method suitable for corpus studies on segmental durations. The method uses an utterance-level normalization approach to capture the pattern of segmental durations within each utterance. This prevents the impact of various problematic variations within the corpora. The normalization is used in a study on final lengthening to show that the results on the effect are not caused by variation in the material. The dissertation shows an implementation and prowess of speech synthesis on a mobile platform. We find that the rule-based method of speech synthesis is a real-time software solution, but the signal generation process slows down the system beyond real time. Future aspects of speech synthesis on limited platforms are discussed. The dissertation considers ethical issues on the development of speech technology. The main focus is on the development of speech synthesis with high naturalness, but the problems and solutions are applicable to any other speech technology approaches.Siirretty Doriast