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Hervé Bourlard

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Related publications (65)

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Finding Information in Multimedia Meeting Records

Hervé Bourlard, Andrei Popescu-Belis

This paper surveys the work carried out within two large consortia, AMI and IM2, on improving access to records of human meetings thanks to multimodal interfaces called meeting browsers. These tools help users navigate through multimedia records containing ...

2012

Applying Multi- and Cross-Lingual Stochastic Phone Space Transformations to Non-Native Speech Recognition

Philip Neil Garner, Hervé Bourlard, Mathew Magimai Doss, David Imseng, John David Scott Dines

In the context of hybrid HMM/MLP Automatic Speech Recognition (ASR), this paper describes an investigation into a new type of stochastic phone space transformation, which maps "source" phone (or phone HMM state) posterior probabilities (as obtained at the ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition

Hervé Bourlard, Weifeng Li

The log-energy parameter, typically derived from a full-band spectrum, is a critical feature commonly used in automatic speech recognition (ASR) systems. However, log-energy is difficult to estimate reliably in the presence of background noise. In this pap ...

Ieee-Inst Electrical Electronics Engineers Inc2013

CNN based Query by Example Spoken Term Detection

Hervé Bourlard, Dhananjay Ram

In this work, we address the problem of query by example spoken term detection (QbE-STD) in zero-resource scenario. State of the art solutions usually rely on dynamic time warping (DTW) based template matching. In contrast, we propose here to tackle the pr ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Automatic Dysarthric Speech Detection Exploiting Pairwise Distance-Based Convolutional Neural Networks

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...

IEEE2021

Low-rank and sparse subspace modeling of speech for DNN based acoustic modeling

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

Towards the goal of improving acoustic modeling for automatic speech recognition (ASR), this work investigates the modeling of senone subspaces in deep neural network (DNN) posteriors using low-rank and sparse modeling approaches. While DNN posteriors are ...

ELSEVIER SCIENCE BV2019

Automatic Recognition of Emergent Social Roles in Small Group Interactions

Hervé Bourlard, Ashtosh Sapru

This paper investigates the automatic recognition of social roles that emerge naturally in small groups. These roles represent a flexible classification scheme that can generalize across different scenarios of small group interaction. We systematically inv ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

Conventional deep neural networks (DNN) for speech acoustic modeling rely on Gaussian mixture models (GMM) and hidden Markov model (HMM) to obtain binary class labels as the targets for DNN training. Subword classes in speech recognition systems correspond ...

Ieee2017

System fusion and speaker linking for longitudinal diarization of TV shows

Hervé Bourlard, Petr Motlicek

Performing speaker diarization while uniquely identifying the speakers in a collection of audio recordings is a challenging task. Based on our previous work on speaker diarization and linking, we developed a system for diarizing longitudinal TV show data s ...

IEEE2016

Improved overlap speech diarization of meeting recordings using long-term conversational features

Hervé Bourlard, Sree Harsha Yella

Overlapping speech is a source of significant errors in speaker diarization of spontaneous meeting recordings. Recent works on speaker diarization have attempted to solve the problem of overlap detection using classifiers trained on acoustic and spatial fe ...

IEEE2013

Multitask adaptation with Lattice-Free MMI for multi-genre speech recognition of low resource languages

Hervé Bourlard, Petr Motlicek

In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre speech recognition of low-resource languages where training data is predominantly conversational speech but test data can be in one of the following genres: news broadcast ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Multilingual Bottleneck Features For Query By Example Spoken Term Detection

Hervé Bourlard, Dhananjay Ram

State of the art solutions to query by example spoken term detection (QbE-STD) rely on bottleneck feature representation of the query and audio document. Here, we present a study on QbE-STD performance using several monolingual as well as multilingual bott ...

IEEE2019

Method, apparatus and computer program product for determining the location of a plurality of speech sources

Volkan Cevher, Hervé Bourlard, Afsaneh Asaei

The present invention discloses a method, apparatus and computer program product for determining the location of a plurality of speech sources in an area of interest, comprising performing an algorithm on a signal issued by either one of said plurality of ...

2012

Privacy-Sensitive Audio Features for Speech/Nonspeech Detection

Hervé Bourlard, Daniel Gatica-Perez, Mathew Magimai Doss, Sree Hari Krishnan Parthasarathi

The goal of this paper is to investigate features for speech/nonspeech detection (SND) having low linguistic information from the speech signal. Towards this, we present a comprehensive study of privacy-sensitive features for SND in multiparty conversation ...

2011

Exploiting Low-dimensional Structures to Enhance DNN based Acoustic Modeling in Speech Recognition

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

We propose to model the acoustic space of deep neural network (DNN) class-conditional posterior probabilities as a union of low- dimensional subspaces. To that end, the training posteriors are used for dictionary learning and sparse coding. Sparse represen ...

IEEE2016

Structured Sparse Coding for Microphone Array Location Calibration

Volkan Cevher, Hervé Bourlard, Afsaneh Asaei

We address the problem of microphone location cali- bration where the sensor positions have a sparse spatial approximation on a discretized grid. We characterize the microphone signals as a sparse vector represented over a codebook of multi-channel signals ...

2012

Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees

Hervé Bourlard, Philip Neil Garner, Afsaneh Asaei, Reza Parhizkar, Mohammadjavad Taghizadeh

This paper addresses the problem of ad hoc microphone array calibration where only partial information about the distances between the microphones is available. We construct a matrix consisting of the pairwise distances and propose to estimate the missing ...

2015

Cross-lingual Adaptation of a CTC-based multilingual Acoustic Model

Philip Neil Garner, Hervé Bourlard, Sibo Tong

Multilingual models for Automatic Speech Recognition (ASR) are attractive as they have been shown to benefit from more training data, and better lend themselves to adaptation to under-resourced languages. However, initialisation from monolingual context-de ...

ELSEVIER SCIENCE BV2018

Subspace Detection of DNN Posterior Probabilities via Sparse Representation for Query by Example Spoken Term Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

We cast the query by example spoken term detection (QbE-STD) problem as subspace detection where query and background subspaces are modeled as union of low-dimensional subspaces. The speech exemplars used for subspace modeling are class-conditional posteri ...

Idiap2016

Phonological Posterior Hashing for Query by Example Spoken Term Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

State of the art query by example spoken term detection (QbE-STD) systems in zero-resource conditions rely on representation of speech in terms of sequences of class-conditional posterior probabilities estimated by deep neural network (DNN). The posteriors ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018