In this paper we present a new approach for topic spotting based on subword units and feature vectors instead of words. In our first approach, we only use vector quantized feature vectors and polygram language models for topic representation. In the second approach, we use phonemes instead

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

This paper deals with the choice of suitable subword units (SWU) for a HMM based speech recognition system. Using demisyllables (including phonemes) as base units, an inventory of domain-specific larger sized subword units, so-called macro-demisyllables (MDS), is created. A quality measure

In this paper, we propose an idea to use subword synthesis units to generate novel word sound of Malay language. The subword synthesis units were carefully created based on Malay phoneme adjacency analysis. The phoneme adjacency analysis was used to find out which adjacent phonemes that would

In this work, we describe a subword unit approach for information retrieval of items by voice. An algorithm based on the minimum description length (MDL) principle converts an index written in terms of words into an index written in terms of phonetic subword units. A speech recognition engine

We propose a novel hidden Markov model (HMM) formalism for automatic derivation of subword units and pronunciation generation using only transcribed speech data. In this approach, the subword units are derived from the clustered context-dependent units in a grapheme based system using maximum

In this paper we introduce the demiphone as a contextual phonetic unit for continuous speech recognition. A phone is divided into two parts: a left demiphone that accounts for the left side coarticulation and a right demiphone that copes with the right side context. This new unit discards

We investigate methods for unsupervised learning of sub-word acoustic units of a language directly from speech. We demonstrate that states of a hidden Markov model “grown ” using a novel modification of the maximum likelihood successive state splitting algorithm correspond very well with the phones

This paper is concerned with the problem of phonetic modeling in a Mandarin keyword spotting system. The task is to detect 20 keywords from continuous speech in the Call Home corpus from the Linguistic Data Consortium (LDC). Different speech units are explored, including whole word, syllable

We describe a method to model pronunciation variation for ASR in a data-driven way, namely by use of automatically derived acoustic subword units. The inventory of units is designed so as to produce maximal separable pronunciation variants of words while at the same time only the most important