I investigated a method for facial expression recognition for a human speaker by using thermal image processing and a speech recognition system. In this study, we improved our speech recognition system to save thermal images at the three timing positions of just before speaking, and just when speaking the phonemes of the first and last vowels. With this method, intentional facial expressions of...

To improve the reliability of telephone-based speaker verification systems, channel compensation is indispensable. However, it is also important to ensure that the channel compensation algorithms in these systems surpress channel variations and enhance interspeaker distinction. This paper addresses this problem by a blind feature-based transformation approach in which the transformation paramet...

Many applications of speech communication and speaker identification suffer from the problem of co-channel speech. This paper deals with a multi-resolution dyadic wavelet transform method for usable segments of co-channel speech detection that could be processed by a speaker identification system. Evaluation of this method is performed on TIMIT database referring to the Target to Interferer Rat...

Voice transformation (VT) aims to change one or more aspects of a speech signal while preserving linguistic information. A subset of VT, Voice conversion (VC) specifically aims to change a source speaker’s speech in such a way that the generated output is perceived as a sentence uttered by a target speaker. Despite many years of research, VC systems still exhibit deficiencies in accurately mimi...

A number of research studies in speaker recognition have recently focused on robustness due to microphone and channel mismatch(e.g., NIST SRE). However, changes in vocal effort, especially whispered speech, present significant challenges in maintaining system performance. Due to the mismatch spectral structure resulting from the different production mechanisms, performance of speaker identifica...

Smoothed estimation and utterance veri cation are introduced into the N-best-based speaker adaptation method. That method is e ective even for speakers whose decodings using speaker-independent (SI) models are error-prone, that is, for speakers for whom adaptation techniques are truly needed. The smoothed estimation improves the performance for such speakers, and the utterance veri cation reduc...

We propose a method for estimating the parameters of SPLICElike transformations from individual utterances so that this type of transformation can be used to normalize acoustic feature vectors for speech recognition on an utterance-by-utterance basis in a similar manner to cepstral mean normalization. We report results on an in-house French language multi-speaker database collected while deploy...

This paper proposes a single-source multi-sample fusion approach to text-independent speaker verification. In conventional speaker verification systems, the scores obtained from claimant’s utterances are averaged and the resulting mean score is used for decision making. Instead of using an equal weight for all scores, this paper proposes assigning a different weight to each score, where the wei...

We propose a technique for generating a large amount of target speaker-like speech features by converting a large amount of prepared speech features of many speakers into features similar to those of the target speaker using a transformation matrix. To generate a large amount of target speaker-like features, the system only needs a very small amount of the target speaker’s utterances. This tech...

In this paper we propose a speaker clustering scheme working in ’Eigenspace’. Speaker models are transformed to a low-dimensional subspace using ’Eigenvoices’. For the speaker clustering procedure simple distance measures, e.g. Euklidean distance can be applied. Moreover, clustering can be accomplished with base models (for Eigenvoice projection) like Gaussian Mixture Models as well as conventi...