Concept

Formant

Related publications (31)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

VTLN Adaptation for Statistical Speech Synthesis

Philip Neil Garner, John David Scott Dines, Hui Liang, Lakshmi Babu Saheer

The advent of statistical speech synthesis has enabled the unification of the basic techniques used in speech synthesis and recognition. Adaptation techniques that have been successfully used in recognition systems can now be applied to synthesis systems t ...

2010

Study of Jacobian Normalization for VTLN

Philip Neil Garner, John David Scott Dines, Lakshmi Babu Saheer

The divergence of the theory and practice of vocal tract length normalization (VTLN) is addressed, with particular emphasis on the role of the Jacobian determinant. VTLN is placed in a Bayesian setting, which brings in the concept of a prior on the warping ...

Idiap2010

VTLN Adaptation for Statistical Speech Synthesis

Philip Neil Garner, John David Scott Dines, Hui Liang, Lakshmi Babu Saheer

Idiap2009

Multi-resolution Spectral Entropy Based Feature for Robust ASR

Hervé Bourlard, Hemant Misra, Shajith Ikbal

Recently, entropy measures at different stages of recognition have been used in automatic speech recognition (ASR) task. In a recent paper, we proposed that formant positions of a spectrum can be captured by multi-resolution spectral entropy feature. In th ...

2005

Multi-resolution Spectral Entropy Based Feature for Robust ASR

Hervé Bourlard, Hemant Misra, Shajith Ikbal

IDIAP2004

HMM inference towards flexible speech recognition

One of the difficulties in Automatic Speech Recognizer (ASR) is the pronunciation variability. Each word (modeled by a baseline phonetic transcription in the ASR dictionary) can be pronounced in many different ways depending on many complex qualitative and ...

IDIAP2003

, ,

This paper investigates possibilities to automatically find a low-dimensional, formant-related physical representation of the speech signal, which is suitable for automatic speech recognition (ASR). This aim is motivated by the fact that formants have been ...

IDIAP2002

, ,

2002

Noise PDF transformation in secondary feature processing

Motivated by the human ability to maintain a high level of speech recognition when large parts of the spectrogram are masked (i.e. dominated) by noise, the original "missing data" (MD) approach to noise robust speech recognition was based on the paradigm w ...

IDIAP2002

HMM2- Extraction of Formant Features and their Use for Robust ASR

Hervé Bourlard, Samy Bengio, Katrin Weber

As recently introduced, an HMM2 can be considered as a particular case of an HMM mixture in which the HMM emission probabilities (usually estimated through Gaussian mixtures or an artificial neural network) are modeled by state-dependent, feature-based HMM ...

2001