Hierarchical clustering of speakers into accents with the ACCDIST metric

Hierarchical clustering of speakers by their pronunciation patterns could be a useful technique for the discovery of accents and the relationships between accents and sociological variables. However it is first necessary to ensure that the clustering is not influenced by the physical characteristics of the speakers. In this study a number of approaches to agglomerative hierarchical clustering of 275 speakers from 14 regional accent groups of the British Isles are formally evaluated. The ACCDIST metric is shown to have superior performance both in terms of accent purity in the cluster tree and in terms of the interpretability of the higher-levels of the tree. Although operating from robust spectral envelope features, the ACCDIST measure also showed the least sensitivity to speaker gender. The conclusion is that, if performed with care, hierarchical clustering could be a useful technique for discovery of accent groups from the bottom up

Dogs perceive and spontaneously normalise formant-related speaker and vowel differences in human speech sounds

Domesticated animals have been shown to recognise basic phonemic information from human speech sounds and to recognise familiar speakers from their voices. However, whether animals can spontaneously identify words across unfamiliar speakers (speaker normalisation) or spontaneously discriminate between unfamiliar speakers across words remains to be investigated. Here, we assessed these abilities in domestic dogs using the habituation-dishabituation paradigm. We found that while dogs habituated to the presentation of a series of different short words from the same unfamiliar speaker, they significantly dishabituated to the presentation of a novel word from a new speaker of the same gender. This suggests that dogs spontaneously categorised the initial speaker across different words. Conversely, dogs who habituated to the same short word produced by different speakers of the same gender significantly dishabituated to a novel word, suggesting that they had spontaneously categorised the word across different speakers. Our results indicate that the ability to spontaneously recognise both the same phonemes across different speakers, and cues to identity across speech utterances from unfamiliar speakers, is present in domestic dogs and thus not a uniquely human trait

Modelling the effects of speech rate variation for automatic speech recognition

Wrede B. Modelling the effects of speech rate variation for automatic speech recognition. Bielefeld (Germany): Bielefeld University; 2002.In automatic speech recognition it is a widely observed phenomenon that variations in speech rate cause severe degradations of the speech recognition performance. This is due to the fact that standard stochastic based speech recognition systems specialise on average speech rate. Although many approaches to modelling speech rate variation have been made, an integrated approach in a substantial system still has be to developed. General approaches to rate modelling are based on rate dependent models which are trained with rate specific subsets of the training data. During decoding a signal based rate estimation is performed according to which the set of rate dependent models is selected. While such approaches are able to reduce the word error rate significantly, they suffer from shortcomings such as the reduction of training data and the expensive training and decoding procedure. However, phonetic investigations show that there is a systematic relationship between speech rate and the acoustic characteristics of speech. In fast speech a tendency of reduction can be observed which can be described in more detail as a centralisation effect and an increase in coarticulation. Centralisation means that the formant frequencies of vowels tend to shift towards the vowel space center while increased coarticulation denotes the tendency of the spectral features of a vowel to shift towards those of its phonemic neighbour. The goal of this work is to investigate the possibility to incorporate the knowledge of the systematic nature of the influence of speech rate variation on the acoustic features in speech rate modelling. In an acoustic-phonetic analysis of a large corpus of spontaneous speech it was shown that an increased degree of the two effects of centralisation and coarticulation can be found in fast speech. Several measures for these effects were developed and used in speech recognition experiments with rate dependent models. A thorough investigation of rate dependent models showed that with duration and coarticulation based measures significant increases of the performance could be achieved. It was shown that by the use of different measures the models were adapted either to centralisation or coarticulation. Further experiments showed that by a more detailed modelling with more rate classes a further improvement can be achieved. It was also observed that a general basis for the models is needed before rate adaptation can be performed. In a comparison to other sources of acoustic variation it was shown that the effects of speech rate are as severe as those of speaker variation and environmental noise. All these results show that for a more substantial system that models rate variations accurately it is necessary to focus on both, durational and spectral effects. The systematic nature of the effects indicates that a continuous modelling is possible

Automatic prosodic analysis for computer aided pronunciation teaching

Correct pronunciation of spoken language requires the appropriate modulation of acoustic characteristics of speech to convey linguistic information at a suprasegmental level. Such prosodic modulation is a key aspect of spoken language and is an important component of foreign language learning, for purposes of both comprehension and intelligibility. Computer aided pronunciation teaching involves automatic analysis of the speech of a non-native talker in order to provide a diagnosis of the learner's performance in comparison with the speech of a native talker. This thesis describes research undertaken to automatically analyse the prosodic aspects of speech for computer aided pronunciation teaching. It is necessary to describe the suprasegmental composition of a learner's speech in order to characterise significant deviations from a native-like prosody, and to offer some kind of corrective diagnosis. Phonological theories of prosody aim to describe the suprasegmental composition of speech..

Production and perception of Libyan Arabic vowels

PhD ThesisThis study investigates the production and perception of Libyan Arabic (LA) vowels by native speakers and the relation between these major aspects of speech. The aim was to provide a detailed acoustic and auditory description of the vowels available in the LA inventory and to compare the phonetic features of these vowels with those of other Arabic varieties. A review of the relevant literature showed that the LA dialect has not been investigated experimentally. The small number of studies conducted in the last few decades have been based mainly on impressionistic accounts. This study consists of two main investigations: one concerned with vowel production and the other with vowel perception. In terms of production, the study focused on gathering the data necessary to define the vowel inventory of the dialect and to explore the qualitative and quantitative characteristics of the vowels contained in this inventory. Twenty native speakers of LA were recorded while reading target monosyllabic words in carrier sentences. Acoustic and auditory analyses were used in order to provide a fairly comprehensive and objective description of the vocalic system of LA. The results showed that phonologically short and long Arabic vowels vary significantly in quality as well as quantity; a finding which is increasingly being reported in experimental studies of other Arabic dialects. Short vowels in LA tend to be more centralised than has been reported for other Arabic vowels, especially with regards to short /a/. The study also looked at the effect of voicing in neighbouring consonants and vowel height on vowel duration, and the findings were compared to those of other varieties/languages. The perception part of the study explored the extent to which listeners use the same acoustic cues of length and quality in vowel perception that are evident in their production. This involved the use of continua from synthesised vowels which varied along duration and/or formant frequency dimensions. The continua were randomised and played to 20 native listeners who took part in an identification task. The results show that, when it comes to perception, Arabic listeners still rely mainly on quantity for the distinction between phonologically long and short vowels. That is, when presented with stimuli containing conflicting acoustic cues (formant frequencies that are typical of long vowels but with short duration or formant frequencies that are typical of short vowels but with long duration), listeners reacted consistently to duration rather than formant frequency. The results of both parts of the study provided some understanding of the LA vowel system. The production data allowed for a detailed description of the phonetic characteristics of LA vowels, and the acoustic space that they occupy was compared with those of other Arabic varieties. The perception data showed that production and perception do not always go hand in hand and that primary acoustic cues for the identification of vowels are dialect- and language-specific

Comparing human and machine vowel classification

In this study we compare human ability to identify vowels with a machine learning approach. A perception experiment for 14 Hungarian vowels in isolation and embedded in a carrier word was accomplished, and a C4.5 decision tree was trained on the same material. A comparison between the identification results of the subjects and the classifier showed that in three of four conditions (isolated vowel quantity and identity, embedded vowel identity) the performance of the classifier was superior and in one condition (embedded vowel quantity) equal to the subjects’ performance. This outcome can be explained by perceptual limits of the subjects and by stimulus properties. The classifier’s performance was significantly weakened by replacing the continuous spectral information by binary 3-Bark thresholds as proposed in phonetic literature [8]. Parts of the resulting decision trees can be interpreted phonetically, which could qualify this classifier as a tool for phonetic research

Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

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