Tone classification of syllable -segmented Thai speech based on multilayer perceptron

Thai is a monosyllabic and tonal language. Thai makes use of tone to convey lexical information about the meaning of a syllable. Thai has five distinctive tones and each tone is well represented by a single F0 contour pattern. In general, a Thai syllable with a different tone has a different lexical meaning. Thus, to completely recognize a spoken Thai syllable, a speech recognition system has not only to recognize a base syllable but also to correctly identify a tone. Hence, tone classification of Thai speech is an essential part of a Thai speech recognition system.;In this study, a tone classification of syllable-segmented Thai speech which incorporates the effects of tonal coarticulation, stress and intonation was developed. Automatic syllable segmentation, which performs the segmentation on the training and test utterances into syllable units, was also developed. The acoustical features including fundamental frequency (F0), duration, and energy extracted from the processing syllable and neighboring syllables were used as the main discriminating features. A multilayer perceptron (MLP) trained by backpropagation method was employed to classify these features. The proposed system was evaluated on 920 test utterances spoken by five male and three female Thai speakers who also uttered the training speech. The proposed system achieved an average accuracy rate of 91.36%

Integrating Prosodics into a Language Model for Spoken Language Understanding of Thai

PACLIC / The University of the Philippines Visayas Cebu College Cebu City, Philippines / November 20-22, 200

Opening up closings - the Ecuadorian way

In the conversation analytic tradition, this paper examines the procedures Ecuadorian Spanish (ES) speakers employ to close telephone conversations. Conversation analysts (cf. Schegloff, 1979) examined telephone talk in American English and that found that conversations are opened and brought to a close by the joint work of participants. Concerning closings, they observed, for example, that participants employ certain procedures to signal their desire to bring the conversation to an end and others to actually close the interaction. They also suggested that the conversational procedures they describe are of a universal character (cf. Schegloff and Sacks, 1974 [1973]). The examination of telephone closings in the present study reveals that similar procedures are employed in Ecuadorian Spanish. Nevertheless, it also highlights some of the features that appear to be characteristic of Ecuadorian Spanish only, that is, that seem to be culture-bound, and thus contests Schegloff and Sacks's unversality claims. The need for a culturally contexted conversation analysis, along the lines proposed by Moerman (1988) is supported here

Explaining the PENTA model: a reply to Arvaniti and Ladd

This paper presents an overview of the Parallel Encoding and Target Approximation (PENTA) model of speech prosody, in response to an extensive critique by Arvaniti & Ladd (2009). PENTA is a framework for conceptually and computationally linking communicative meanings to fine-grained prosodic details, based on an articulatory-functional view of speech. Target Approximation simulates the articulatory realisation of underlying pitch targets – the prosodic primitives in the framework. Parallel Encoding provides an operational scheme that enables simultaneous encoding of multiple communicative functions. We also outline how PENTA can be computationally tested with a set of software tools. With the help of one of the tools, we offer a PENTA-based hypothetical account of the Greek intonational patterns reported by Arvaniti & Ladd, showing how it is possible to predict the prosodic shapes of an utterance based on the lexical and postlexical meanings it conveys

Deep Learning for Automatic Assessment and Feedback of Spoken English

Growing global demand for learning a second language (L2), particularly English, has led to considerable interest in automatic spoken language assessment, whether for use in computerassisted language learning (CALL) tools or for grading candidates for formal qualifications. This thesis presents research conducted into the automatic assessment of spontaneous nonnative English speech, with a view to be able to provide meaningful feedback to learners. One of the challenges in automatic spoken language assessment is giving candidates feedback on particular aspects, or views, of their spoken language proficiency, in addition to the overall holistic score normally provided. Another is detecting pronunciation and other types of errors at the word or utterance level and feeding them back to the learner in a useful way. It is usually difficult to obtain accurate training data with separate scores for different views and, as examiners are often trained to give holistic grades, single-view scores can suffer issues of consistency. Conversely, holistic scores are available for various standard assessment tasks such as Linguaskill. An investigation is thus conducted into whether assessment scores linked to particular views of the speaker’s ability can be obtained from systems trained using only holistic scores. End-to-end neural systems are designed with structures and forms of input tuned to single views, specifically each of pronunciation, rhythm, intonation and text. By training each system on large quantities of candidate data, individual-view information should be possible to extract. The relationships between the predictions of each system are evaluated to examine whether they are, in fact, extracting different information about the speaker. Three methods of combining the systems to predict holistic score are investigated, namely averaging their predictions and concatenating and attending over their intermediate representations. The combined graders are compared to each other and to baseline approaches. The tasks of error detection and error tendency diagnosis become particularly challenging when the speech in question is spontaneous and particularly given the challenges posed by the inconsistency of human annotation of pronunciation errors. An approach to these tasks is presented by distinguishing between lexical errors, wherein the speaker does not know how a particular word is pronounced, and accent errors, wherein the candidate’s speech exhibits consistent patterns of phone substitution, deletion and insertion. Three annotated corpora x of non-native English speech by speakers of multiple L1s are analysed, the consistency of human annotation investigated and a method presented for detecting individual accent and lexical errors and diagnosing accent error tendencies at the speaker level

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

Tone and intonation: introductory notes and practical recommendations

International audienceThe present article aims to propose a simple introduction to the topics of (i) lexical tone, (ii) intonation, and (iii) tone-intonation interactions, with practical recommendations for students. It builds on the authors' observations on various languages, tonal and non-tonal; much of the evidence reviewed concerns tonal languages of Asia. With a view to providing beginners with an adequate methodological apparatus for studying tone and intonation, the present notes emphasize two salient dimensions of linguistic diversity. The first is the nature of the lexical tones: we review the classical distinction between (i) contour tones that can be analyzed into sequences of level tones, and (ii) contour tones that are non-decomposable (phonetically complex). A second dimension of diversity is the presence or absence of intonational tones: tones of intonational origin that are formally identical with lexical (and morphological) tones

Hakka tone training for native speakers of tonal and nontonal languages

Language learning becomes increasingly difficult when novel linguistic features are introduced. Studies have shown that learners from various language backgrounds can be trained to perceive lexical tone, which assigns meaning to words using variations in pitch. In this thesis, we investigated whether native speakers of tonal Mandarin Chinese and tonal Vietnamese outperformed native speakers of nontonal English when learning Hakka Chinese tones following five sessions of tone training, and whether the complexity (i.e., density) of a listener’s native tone inventory facilitated nonnative tone learning. All groups improved in tone identification and tone word learning following training, with improvements persisting three weeks following the cessation of training. Although both tonal groups outperformed the English group in most tasks, the Mandarin group showed the most consistent advantages over the English group across tasks. Findings suggest that tone experience bolsters tone learning, but density of the tone inventory does not provide an advantage. Confusion patterns offer detailed insight of the interaction between nonnative tones and native tonal and intonational categories