In this paper, we present some recent improvements in our automatic speech segmentation system, which only needs the speech signal and the phonetic sequence of each sentence of a corpus to be trained. It estimates a GMM by using all the sentences of the training subcorpus, where each Gaussian distribution represents an acoustic class, which probability densities are combined with a set of condi...

This paper describes a novel approach to speech recognition which is based on phonetic features as basic recognition units and the delayed synchronisation of these features within a higher-level prosodic domain, viz. the syllable. The object of this approach is to avoid a rigid segmentation of the speech signal as it is usually carried out by standard segment-based recognition systems. The arch...

It is well known that listeners adapt, in some sense, to speech that they have recently heard. Words spoken in recently heard voices or accents are recognized more quickly and accurately (Mullennix et al. 1989; Goldinger 1996; Nygaard & Pisoni 1998; Maye et al. 2003; Kraljic and Samuel 2006, 2007; Smith 2007; see Nygaard 2008 for a review). And listeners can become attuned to novel phonetic cha...

This paper investigates the feasibility of using subword unit representations for spoken document retrieval as an alternative to using words generated by either keyword spotting or word recognition. Our investigation is motivated by the observation that word-based retrieval approaches face the problem of either having to know the keywords to search for a priori, or requiring a very large recogn...

Infants segment words from fluent speech during the same period when they are learning phonetic categories, yet accounts of phonetic category acquisition typically ignore information about the words in which sounds appear. We use a Bayesian model to illustrate how feedback from segmented words might constrain phonetic category learning by providing information about which sounds occur together ...

Acoustic Modeling in today’s emotion recognition engines employs general models independent of the spoken phonetic content. This seems to work well enough given sufficient instances to cover for a broad variety of phonetic structures and emotions at the same time. However, data is usually sparse in the field and the question arises whether unit specific models as word emotion models could outpe...

This paper describes the pilot study of phonetic segmentation applied to Nijmegen Corpus of Casual Czech (NCCCz). This corpus contains informal speech of strong spontaneous nature which influences the character of produced speech at various levels. This work is the part of wider research related to the analysis of pronunciation reduction in such informal speech. We present the analysis of the a...

In this paper the transcription and evaluation of the corpus DIMEx100 for Mexican Spanish is presented. First we describe the corpus and explain the linguistic and computational motivation for its design and collection process; then, the phonetic antecedents and the alphabet adopted for the transcription task are presented; the corpus has been transcribed at three different granularity levels, ...

Accurate phone-level segmentation of speech remains an important task for many subfields of speech research. We investigate techniques for boosting the accuracy of automatic phonetic segmentation based on HMM acoustic-phonetic models. In prior work [25] we were able to improve on state-of-the-art alignment accuracy by employing special phone boundary HMM models, trained on phonetically segmente...