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Petr Motlicek

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Related publications (47)

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Automatic Speech Recognition Benchmark for Air-Traffic Communications

Petr Motlicek

Advances in Automatic Speech Recognition (ASR) over the last decade opened new areas of speech-based automation such as in Air-Traffic Control (ATC) environments. Currently, voice communication and Controller Pilot Data Link Communications are the only way ...

ISCA2020

Exploiting foreign resources for DNN-based ASR

Petr Motlicek, Philip Neil Garner, David Imseng

Manual transcription of audio databases for the development of automatic speech recognition (ASR) systems is a costly and time-consuming process. In the context of deriving acoustic models adapted to a specific application, or in low-resource scenarios, it ...

2015

Deep Neural Networks for Multiple Speaker Detection and Localization

Jean-Marc Odobez, Petr Motlicek, Weipeng He

We propose to use neural networks for simultaneous detection and localization of multiple sound sources in human-robot interaction. In contrast to conventional signal processing techniques, neural network-based sound source localization methods require few ...

2018

The MuMMER Data Set for Robot Perception in Multi-party HRI Scenarios

Jean-Marc Odobez, Petr Motlicek, Olivier Canévet

This paper presents the MuMMER data set, a data set for human-robot interaction scenarios that is available for research purposes% It comprises 1 h 29 min of multimodal recordings of people interacting with the social robot Pepper in entertainment scenario ...

IEEE2020

Idiap Submission to Swiss-German Language Detection Shared Task

Petr Motlicek

Language detection is a key part of the NLP pipeline for text processing. The task of automatically detecting languages belonging to disjoint groups is relatively easy. It is considerably challenging to detect languages that have similar origins or dialect ...

CEUR Workshop Proceedings2020

INTRA-CLASS COVARIANCE ADAPTATION IN PLDA BACK-ENDS FOR SPEAKER VERIFICATION

Petr Motlicek, Subhadeep Dey

Multi-session training conditions are becoming increasingly common in recent benchmark datasets for both text-independent and text-dependent speaker verification. In the state-of-the-art i-vector framework for speaker verification, such conditions are addr ...

Ieee2017

The TA2 Database – A Multi-Modal Database From Home Entertainment

Petr Motlicek

This paper presents a new database containing high-definition audio and video recordings in a rather unconstrained video-conferencing-like environment. The database consists of recordings of people sitting around a table in two separate rooms communicating ...

2012

Joint Localization and Classification of Multiple Sound Sources Using a Multi-task Neural Network

Jean-Marc Odobez, Petr Motlicek, Weipeng He

We propose a novel multi-task neural network-based approach for joint sound source localization and speech/non-speech classification in noisy environments. The network takes raw short time Fourier transform as input and outputs the likelihood values for th ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

A Bayesian Approach To Inter-Task Fusion For Speaker Recognition

Petr Motlicek, Subhadeep Dey

In i-vector based speaker recognition systems, back-end classifiers are trained to factor out nuisance information and retain only the speaker identity. As a result, variabilities arising due to gender, language and accent ( among many others) are suppress ...

IEEE2019

Real-Time Audio-Visual Analysis for Multiperson Videoconferencing

Petr Motlicek, Hervé Bourlard, Jean-Marc Odobez

We describe the design of a system consisting of several state-of-the-art real-time audio and video processing components enabling multimodal stream manipulation (e.g., automatic online editing for multiparty videoconferencing applications) in open, uncons ...

2013

Towards a breakthrough Speaker Identification approach for Law Enforcement Agencies: SIIP

Petr Motlicek

This paper describes SIIP (Speaker Identification Integrated Project) a high performance innovative and sustainable Speaker Identification (SID) solution, running over large voice samples database. The solution is based on development, integration and fusi ...

2017

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Petr Motlicek, Juan Pablo Zuluaga Gomez

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken ...

MDPI2023

A Simple Continuous Pitch Estimation Algorithm

Petr Motlicek, Philip Neil Garner

Recent work in text to speech synthesis has pointed to the benefit of using a continuous pitch estimate; that is, one that records pitch even when voicing is not present. Such an approach typically requires interpolation. The purpose of this paper is to sh ...

IEEE Institute of Electrical and Electronics Engineers2013

Boosting of contextual information in ASR for air-traffic call-sign recognition

Petr Motlicek, Juan Pablo Zuluaga Gomez

Contextual adaptation of ASR can be very beneficial for multi-accent and often noisy Air-Traffic Control (ATC) speech. Our focus is call-sign recognition, which can be used to track conversations of ATC operators with individual airplanes. We developed a t ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Classification and Regression of Cognitive and Motivational Style from Text

Petr Motlicek

In this paper, we describe the participation of the Idiap Research Institute at GermEval 2020 shared task on the Classification and Regression of Cognitive and Motivational style from Text, specifically on subtask 2, Classification of the Operant Motive Te ...

2020

Multi-task Neural Network for Robust Multiple Speaker Embedding Extraction

Jean-Marc Odobez, Petr Motlicek, Weipeng He

This paper introduces a novel approach for extracting speaker embeddings from audio mixtures of multiple overlapping voices. This approach is based on a multi-task neural network. The network first extracts a latent feature for each direction. This feature ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

A Comparison of Methods for OOV-Word Recognition on a New Public Dataset

Petr Motlicek

A common problem for automatic speech recognition systems is how to recognize words that they did not see during training. Currently there is no established method of evaluating different techniques for tackling this problem. We propose using the CommonVoi ...

IEEE Signal Processing Society2021

ODIANLP's Participation in WAT2020

Petr Motlicek

This paper describes the team (“ODI-ANLP”)’s submission to WAT 2020. We have participated in the English→HindiMultimodal task and Indic task. We have used the state-of-the-art Transformer model for the translation task and Incep-tionResNetV2 for the Hindi ...

ACL2020

Idiap & UAM participation at GermEval 2020: Classification and Regression of Cognitive and Motivational Style from Text

Petr Motlicek

Hamburg University2020

Supervised domain adaptation for text-independent speaker verification using limited data

Sébastien Marcel, Petr Motlicek

ISCA2020