Recherche

Afficher tous les résultats pour

Accueil

Personne

Afsaneh Asaei

Cette personne a quitté l’EPFL

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (30)

Page 1 sur 2

On Structured Sparsity of Phonological Posteriors for Linguistic Parsing

Hervé Bourlard, Afsaneh Asaei

The speech signal conveys information on different time scales from short (20--40 ms) time scale or segmental, associated to phonological and phonetic information to long (150--250 ms) time scale or supra segmental, associated to syllabic and prosodic info ...

2016

Verified Speaker Localization Utilizing Voicing Level in Split-bands

Afsaneh Asaei, Mohammadjavad Taghizadeh

This paper proposes a joint verification-localization structure based on split-band analysis of speech signal and the mixed voicing level. To address the problems in reverberant acoustic environments, a new fundamental frequency estimation algorithm is pro ...

2009

Spatial Sound Localization via Multipath Euclidean Distance Matrix Recovery

Philip Neil Garner, Hervé Bourlard, Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

A novel localization approach is proposed in order to find the position of an individual source using recordings of a single microphone in a reverberant enclosure. The multipath propagation is modeled by multiple virtual microphones as images of the actual ...

Ieee-Inst Electrical Electronics Engineers Inc2015

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

Volkan Cevher, Hervé Bourlard, Afsaneh Asaei, Saeid Haghighatshoar, Mohammadjavad Taghizadeh

We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized signals by projecting the microphone array recordings into the array manifolds ...

Institute of Electrical and Electronics Engineers2016

Phonetic Subspace Features for Improved Query by Example Spoken Term Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

This paper addresses the problem of detecting speech utterances from a large audio archive using a simple spoken query, hence referring to this problem as "Query by Example Spoken Term Detection" (QbE-STD). This still open pattern matching problem has been ...

2018

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

We propose an information theoretic framework for quantitative assessment of acoustic models used in hidden Markov model (HMM) based automatic speech recognition (ASR). The HMM backend expects that (i) the acoustic model yields accurate state conditional e ...

ELSEVIER2020

Sparse Modeling of Neural Network Posterior Probabilities for Exemplar-based Speech Recognition

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

In this paper, a compressive sensing (CS) perspective to exemplar-based speech processing is proposed. Relying on an analytical relationship between CS formulation and statistical speech recognition (Hidden Markov Models HMM), the automatic speech recognit ...

2016

Structured Sparsity Models for Reverberant Speech Separation

Volkan Cevher, Hervé Bourlard, Afsaneh Asaei, Mohammad Golbabaee

We tackle the multi-party speech recovery problem through modeling the acoustic of the reverberant chambers. Our approach exploits structured sparsity models to perform room modeling and speech recovery. We propose a scheme for characterizing the room acou ...

2014

Far-field ASR Using Low-rank and Sparse Soft Targets from Parallel Data

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

Far-field automatic speech recognition (ASR) of conversational speech is often considered to be a very challenging task due to the poor quality of alignments available for training the DNN acoustic models. A common way to alleviate this problem is to use c ...

IEEE2018

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Hervé Bourlard, Afsaneh Asaei

Phonological features extracted by neural network have shown interesting potential for low bit rate speech vocoding. The span of phonological features is wider than the span of phonetic features, and thus fewer frames need to be transmitted. Moreover, the ...

2015

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

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

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

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

Perceptual Information Loss due to Impaired Speech Production

Hervé Bourlard, Afsaneh Asaei

Phonological classes define articulatory-free and articulatory-bound phone attributes. Deep neural network is used to estimate the probability of phonological classes from the speech signal. In theory, a unique combination of phone attributes form a phonem ...

2017

Manifold Sparse Beamforming

Volkan Cevher, Afsaneh Asaei, Baran Gözcü

We consider the minimum variance distortionless response (MVDR) beamforming problems where the array covariance matrix is rank deficient. The conventional approach handles such rank-deficiencies via diagonal loading on the covariance matrix. In this settin ...

2013

Model-based Sparse Component Analysis for Reverberant Speech Localization

Volkan Cevher, Hervé Bourlard, Afsaneh Asaei, Mohammadjavad Taghizadeh

In this paper, the problem of multiple speaker localization via speech separation based on model-based sparse recovery is studies. We compare and contrast computational sparse optimization methods incorporating harmonicity and block structures as well as a ...

2014

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