Search Results for author:
Found 17 papers, 6 papers with code
One model to rule them all ? Towards End-to-End Joint Speaker Diarization and Speech Recognition
This paper presents a novel framework for joint speaker diarization (SD) and automatic speech recognition (ASR), named SLIDAR (sliding-window diarization-augmented recognition).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
An enhanced system for the detection and active cancellation of snoring signals
Snoring is a common disorder that affects people's social and marital lives.
A Time-Frequency Generative Adversarial based method for Audio Packet Loss Concealment
Packet loss is a major cause of voice quality degradation in VoIP transmissions with serious impact on intelligibility and user experience.
The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios
The CHiME challenges have played a significant role in the development and evaluation of robust automatic speech recognition (ASR) systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
An Experimental Review of Speaker Diarization methods with application to Two-Speaker Conversational Telephone Speech recordings
We found that, among all methods considered, EEND-vector clustering (EEND-VC) offers the best trade-off in terms of computing requirements and performance.
End-to-End Integration of Speech Separation and Voice Activity Detection for Low-Latency Diarization of Telephone Conversations
Recent works show that speech separation guided diarization (SSGD) is an increasingly promising direction, mainly thanks to the recent progress in speech separation.
Conversational Speech Separation: an Evaluation Study for Streaming Applications
Continuous speech separation (CSS) is a recently proposed framework which aims at separating each speaker from an input mixture signal in a streaming fashion.
Low-Latency Speech Separation Guided Diarization for Telephone Conversations
In particular, we compare two low-latency speech separation models.
Learning Filterbanks for End-to-End Acoustic Beamforming
We perform a detailed analysis using the recent Clarity Challenge data and show that by using learnt filterbanks it is possible to surpass oracle-mask based beamforming for short windows.
Deep Optimization of Parametric IIR Filters for Audio Equalization
This paper describes a novel Deep Learning method for the design of IIR parametric filters for automatic audio equalization.
Graph-based Representation of Audio signals for Sound Event Classification
In recent years there has been a considerable rise in interest towards Graph Representation and Learning techniques, especially in such cases where data has intrinsically a graph- like structure: social networks, molecular lattices, or semantic interactions, just to name a few.
Learning to Rank Microphones for Distant Speech Recognition
Fully exploiting ad-hoc microphone networks for distant speech recognition is still an open issue.
Real-World Anomaly Detection by using Digital Twin Systems and Weakly-Supervised Learning
The approaches make use of a Digital Twin to generate a training dataset which simulates the normal operation of the machinery, along with a small set of labeled anomalous measurement from the real machinery.
The Speed Submission to DIHARD II: Contributions & Lessons Learned
This paper describes the speaker diarization systems developed for the Second DIHARD Speech Diarization Challenge (DIHARD II) by the Speed team.
Transfer Learning for Non-Intrusive Load Monitoring
It is not clear if the method could be generalised or transferred to different domains, e. g., the test data were drawn from a different country comparing to the training data.
Polyphonic Sound Event Detection by using Capsule Neural Network
Artificial sound event detection (SED) has the aim to mimic the human ability to perceive and understand what is happening in the surroundings.
A Multi-Stage Algorithm for Acoustic Physical Model Parameters Estimation
In this work we refine previous results by introducing the former approach in a multi-stage algorithm that also adds heuristics and a stochastic optimization method operating on objective cost functions based on psychoacoustics.
