In this paper we present a novel scheme for phoneme recognition in continuous speech using inhomogeneous hidden Markov models (IHMMs). IHMMs can capture the temporal structure of phonemes and inter-phonemic temporal relationships effectively, with their duration dependent state transition probabilities. A two stage IHMM is proposed to capture the variabilities in speech effectively for phoneme ...

Collections of speech documents can be searched using speech retrieval, in which the documents are processed by a speech recogniser to give text that can be searched by standard text retrieval techniques. Recognition is the translation of speech signals into either words or subword units such as phonemes. We investigated the use of a phoneme-based recogniser to obtain phoneme sequences. We foun...

This paper describes an approach for combining phoneme and word recognition to produce an accurate N-best list of hypotheses. We run two decoding threads in parallel. The first performs phoneme recognition, while the other performs word recognition on the same recorded utterance. The output of the word recognition thread is returned as the most likely hypothesis, and the result of the phoneme r...

This paper applies the Competitive Neural Tree (CNeT) method to phoneme recognition, a pattern classiication problem. CNeTs combine the advantages of Decision Trees and Competitive Neural Networks. The CNeT algorithm works by hierarchically clustering given examples while growing a tree. Diierent search methods, as well as stopping and splitting criteria are discussed. The CNeT algorithm allows...

We present a feature extraction technique based on static and dynamic modulation spectrum derived from long-term envelopes in sub-bands. Estimation of the sub-band temporal envelopes is done using Frequency Domain Linear Prediction (FDLP). These sub-band envelopes are compressed with a static (logarithmic) and dynamic (adaptive loops) compression. The compressed sub-band envelopes are transform...

1 Test normalization (T-Norm) is a score normalization technique that is regularly and successfully applied in the context of text-independent speaker recognition. It is less frequently applied, however, to text-dependent or textprompted speaker recognition, mainly because its improvement in this context is more modest. In this paper we present a novel way to improve the performance of T-Norm f...