Publications associées à Speech coding

Sparse Autoencoders for Speech Modeling and Recognition

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Julian David Fritsch

Atypical aspects in speech concern speech that deviates from what is commonly considered normal or healthy. In this thesis, we propose novel methods for detection and analysis of these aspects, e.g. to monitor the temporary state of a speaker, diseases tha ...

EPFL2023

Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?

Mathew Magimai Doss, Eklavya Sarkar

Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an embedding space. This implies that the utility of such representations is no ...

ISCA2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Anne-Claire Marie Billault--Roux, Gionata Ghiggi

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

On Breathing Pattern Information in Synthetic Speech

Mathew Magimai Doss, Zohreh Mostaani

The respiratory system is an integral part of human speech production. As a consequence, there is a close relation between respiration and speech signal, and the produced speech signal carries breathing pattern related information. Speech can also be gener ...

ISCA-INT SPEECH COMMUNICATION ASSOC2022

Learnable Wavelet Packet Transform for Data-Adapted Spectrograms

Olga Fink, Gaëtan Michel Frusque

Capturing high-frequency data concerning the condition of complex systems, e.g. by acoustic monitoring, has become increasingly prevalent. Such high-frequency signals typically contain time dependencies ranging over different time scales and different type ...

2022

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

Alexandre Schmid, Lizeth Gonzalez Carabarin

Model compression techniques have lead to a reduction of size and number of computations of Deep Learning models. However, techniques such as pruning mostly lack of a real co-optimization with hardware platforms. For instance, implementing unstructured pru ...

IEEE2022

Automatic pathological speech assessment

Parvaneh Janbakhshi

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

EPFL2022

Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering

Mathew Magimai Doss, Eklavya Sarkar

Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source ...

ISCA2022

Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-specific Scaling

Paolo Prandoni, Natalia Nessler, Milos Cernak

In communication systems, it is crucial to estimate the perceived quality of audio and speech. The industrial standards for many years have been PESQ, 3QUEST, and POLQA, which are intrusive methods. This restricts the possibilities of using these metrics i ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Benchmarking of objective quality metrics for point cloud compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Evangelos Alexiou

Point cloud is a promising imaging modality for the representation of 3D media. The vast volume of data associated with it requires efficient compression solutions, with lossy algorithms leading to larger bit-rate savings at the expense of visual impairmen ...

IEEE2021

Utterance Verification-Based Dysarthric Speech Intelligibility Assessment Using Phonetic Posterior Features

Mathew Magimai Doss, Julian David Fritsch

In the literature, the task of dysarthric speech intelligibility assessment has been approached through development of different low-level feature representations, subspace modeling, phone confidence estimation or measurement of automatic speech recognitio ...

IEEE Institute of Electrical and Electronics Engineers2021

Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings

Mathew Magimai Doss, Zohreh Mostaani, Venkata Srikanth Nallanthighal

Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a system ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Novel Methods for Incorporating Prior Knowledge for Automatic Speech Assessment

Subrahmanya Pavankumar Dubagunta

Speech signal conveys several kinds of information such as a message, speaker identity, emotional state of the speaker and social state of the speaker. Automatic speech assessment is a broad area that refers to using automatic methods to predict human judg ...

EPFL2021

Many Are The Ways to Learn: Identifying multi-modal behavioral profiles of collaborative learning in constructivist activities

Pierre Dillenbourg, Barbara Bruno, Jauwairia Nasir, Aditi Kothiyal

Understanding how learners engage with learning technologies, and its relation with their learning, is crucial to the design of effective learning interventions. Assessing the learners’ state however, is non-trivial. Research suggests that performance is n ...

2021

Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing

Pierre Anton Beckmann, Milos Cernak

Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech representation were developed to foster automatic speech recognition. Up to ...

EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP2021

Multilingual and Unsupervised Subword Modeling for Zero-Resource Languages

Enno Hermann

Subword modeling for zero-resource languages aims to learn low-level representations of speech audio without using transcriptions or other resources from the target language (such as text corpora or pronunciation dictionaries). A good representation should ...

2021

Automatic Pathological Speech Intelligibility Assessment Exploiting Subspace-Based Analyses

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Competitive state-of-the-art automatic pathological speech intelligibility measures typically rely on regression training on a large number of features, require a large amount of healthy speech training data, or are applicable only to phonetically balanced ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Cooperative Data Exchange and Private Information Retrieval

Su Li

Coding techniques have been well studied and used for improving communication quality by combating noise and mitigating interference. Recently, it has been shown that the same coding techniques can also be exploited to further improve communication perform ...

EPFL2020

Image Compression and Quality Assessment using Convolutional Neural Networks

Pinar Akyazi

The rapid development of digital imaging and video has placed visual contents in the heart of our lives. Digital multimedia span a vast number of areas from business to leisure, including but not limited to education, medicine, accessibility, training, adv ...

EPFL2020