We present a 1000-word continuous speech recognition (CSR) system that operates in real time on a personal computer (PC). The system, designed for large vocabulary natural language tasks, makes use of phonetic Hidden Markov models (HMM) and incorporates acoustic, phonetic, and linguistic sources of knowledge to achieve high recognition performance. We describe the various components of this sys...

In this paper, we discuss automatically generating a phonetic pronunciation from an orthographic spelling of words. The letter-sequence to phoneme-sequence mapping is useful in a variety of contexts, including text-to-speech applications, automatic spelling correction, and generating a pronunciation lexicon for a new training dataset which contains out-of-vocabulary words. A system based on hid...

A multivariate-state HMM | an HMM with a vector state variable | can be used to nd jointly optimal phonetic and formant transcriptions of an utterance. The complexity of searching a multivariate state space using the BaumWelch algorithm is substantial, but may be signi cantly reduced if the formant frequencies are assumed to be conditionally independent given knowledge of the phone. Operating w...

A multivariat,e-state HMM an HMM with a vector state variable can be used to find jointly optimal phonetic and formant transcriptions of an utterance. The complexity of searching a multivariate state space using the BaumWelch algorithm is substantial, but may be significantly reduced if the formant frequencies are assumed to be conditionally independent given knowledge of the phone. Operating w...

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, ...

Adult speech perception is tuned to efficiently process native phonetic categories, causing difficulties with certain non-native categories. For example, Japanese has no equivalent of the distinction between American English /r/ and /l/ and native speakers of Japanese have a hard time discriminating between these two sounds. Here, we ask whether standard Automatic Speech Recognition (ASR) syste...

Computer-assisted pronunciation tutoring (CAPT) methods have been well-established in research and education. Common system approaches include the phonetic quality assessment, highlight problematic sections in the speech signal and usually rely on automatic speech recognition (ASR) regarding the target language L2. The contribution deals with the audiovisual CAPT system AzAR. An extensive feedb...

(3) The Spoken Language Group at MIT's Laboratory for Computer Science also reported results for both the RM and ATIS SPREC test material [3]. The MIT SUMMIT system is a "segment-based" speech recognition system, including a front end that incorporates a model of the auditory system, a hierarchical segmentation algorithm to identify a network of possible acoustical segments, segmental measureme...

The processes that underlie perception of consonants and vowels are specifically phonetic, distinct from those that localize sources and assign auditory qualities to the sound from each source. This specialization, or module, increases the rate of information flow, establishes the parity between sender and receiver that every communication system must have, and provides for the natural developm...