Speaker: Francesca Ronchini Date and place: January 28, 2021 at 10:15, VISIO-CONFERENCE Abstract: Sound Event Localization and Detection refers to the problem of identifying the presence of independent or temporally-overlapped sound sources, correctly identifying to which sound class it belongs, and estimating their spatial directions while they are active. In the last years, neural networks …
Category: Seminars
Jan 21
CRNN vs. Self-Attention in Source Localization and an Introduction of the Project HAIKUS
Speaker: Prerak Srivastava Date and place: January 21, 2021 at 10:15, VISIO-CONFERENCE Abstract: The seminar will consist of two parts, the first part will be related to DOA estimation work done during my master internship, and the latter part will describe some preliminary results about the project HAIKUS. Recently, RNN based CRNN architecture made the state …
Jan 14
Complex-valued and hybrid models for audio processing
Speaker: Paul Magron Date and place: January 14, 2021 at 10:30, VISIO-CONFERENCE Abstract: In this talk, I will give an overview of my work, which main application is sound source separation, the task of automatically extracting constitutive components from their observed mixture in an audio recording. I will address it in the time-frequency domain, which …
Jan 07
End-to-End Spoken Language Understanding and Privacy Preserving Speech Processing
Speaker: Natalia Tomashenko Date and place: January 7, 2021 at 10:30, VISIO-CONFERENCE Abstract: This talk is related to two different topics: (1) e2e SLU from speech and (2) privacy preserving speech processing, as well as to the discussion of challenges of these research areas and perspective research directions. (1) E2e SLU from speech focuses on …
Dec 17
Semi-supervised and Weakly Supervised Training of Speech Recognition Models
Speaker: Imran Sheikh Date and place: December 17, 2020 at 10:30, VISIO-CONFERENCE Abstract: Automatic Speech Recognition (ASR) is now available in the form of cloud services as well as deployable open-source tools. However, poor performance due to mismatch with the domain of end applications still limits their usage; especially with limited amount of labeled/unlabelled in-domain …
Dec 03
Implicit and explicit phase modeling in deep learning-based source separation
Speaker: Manu Pariente Date and place: December 3, 2020 at 10:30, VISIO-CONFERENCE Abstract: Speech enhancement and separation have recently seen great progress thanks to deep learning-based discriminative methods.In particular, time domain methods relying on learned filterbanks achieve state-of-the-art performance by implicitly modeling phase and amplitude. Despite current efforts against those limitations, these methods produce very …
Nov 19
Non-native speech recognition
Speaker: Ismaël Bada Date and place: November 19, 2020 at 10:30, VISIO-CONFERENCE Abstract: We propose a method for lexicon adaptation in order to improve the automatic speech recognition (ASR) of non-native speakers. ASR suffers from a significant drop in performance when it is used to recognize the speech of non-native speakers, since the phonemes of …
Nov 12
Label Propagation-Based Semi-Supervised Learningfor Hate Speech Classification
Speaker: Ashwin Geet D’Sa Date and place: November 12, 2020 at 10:30, VISIO-CONFERENCE Abstract: Research on hate speech classification has received increased attention. In real-life scenarios, a small amount of labeled hate speech data is available to train a reliable classifier. Semi-supervised learning takes advantage ofa small amount of labeled data and a large amount of unlabeled data. …
Nov 05
MRI of the Vocal Tract and Articulators’ Automatic Delineation
Speaker: Karyna Isaieva Date and place:November 5, 2020 at 10:30, VISIO-CONFERENCE Abstract: MRI is a very popular technology that enables fully non-invasive and non-ionizing investigation of the vocal tract. It has multiple applications including studies of healthy speech as well as some medical applications (pathological speech studies, swallowing, etc.). We acquired a database of 10 …
Oct 22
DNN-based distributed mask estimation for speech enhancement in unconstrained microphone arrays
Speaker: Nicolas Furnon Date and place: October 22, 2020 at 10:30 -A008 + VISIO-CONFERENCE Abstract: Deep neural network (DNN)-based speech enhancement algorithms in microphone arrays have now proven to be efficient solutions to speech understanding and speech recognition in noisy environments. However, in the context of ad-hoc microphone arrays, many challenges remain and raise the …
