Concept
Phonotaxe
Publications associées (20)
Articulatory feature based continuous speech recognition using probabilistic lexical modeling
Phonological studies suggest that the typical subword units such as phones or phonemes used in automatic speech recognition systems can be decomposed into a set of features based on the articulators used to produce the sound. Most of the current approaches ...
Elsevier2016Syllabic Pitch Tuning for Neutral-to-Emotional Voice Conversion
Milos Cernak, Lakshmi Babu Saheer
Prosody plays an important role in both identification and synthesis of emotionalized speech. Prosodic features like pitch are usually estimated and altered at a segmental level based on short windows of speech (where the signal is expected to be quasi-sta ...
Idiap2015Joint Phoneme Segmentation Inference and Classification using CRFs
Ronan Collobert, Dimitri Palaz
State-of-the-art phoneme sequence recognition systems are based on hybrid hidden Markov model/artificial neural networks (HMM/ANN) framework. In this framework, the local classifier, ANN, is typically trained using Viterbi expectation-maximization algorith ...
2014Articulatory Feature based Continuous Speech Recognition using Probabilistic Lexical Modeling
Phonological studies suggest that the typical subword units such as phones or phonemes used in automatic speech recognition systems can be decomposed into a set of features based on the articulators used to produce the sound. Most of the current approaches ...
Idiap2014Syllable-based Pitch Encoding for Low Bit Rate Speech Coding with Recognition/Synthesis Architecture
Philip Neil Garner, Milos Cernak
Current HMM-based low bit rate speech coding systems work with phonetic vocoders. Pitch contour coding (on frame or phoneme level) is usually fairly orthogonal to other speech coding parameters. We make an assumption in our work that the speech signal cont ...
Idiap2013Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach
There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...
Idiap2013Improving Grapheme-based ASR by Probabilistic Lexical Modeling Approach
There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...
2013Probabilistic Lexical Modeling and Unsupervised Training for Zero-Resourced ASR
Ramya Rasipuram, Marzieh Razavi
Standard automatic speech recognition (ASR) systems rely on transcribed speech, language models, and pronunciation dictionaries to achieve state-of-the-art performance. The unavailability of these resources constrains the ASR technology to be available for ...
2013Hierarchical Multilayer Perceptron based Language Identification
Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron ...
Idiap2010Hierarchical Multilayer Perceptron based Language Identification
Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron ...
2010