Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …
learning has dramatically revolutionized speaker recognition. However, there is lack of …
A comprehensive survey on model compression and acceleration
T Choudhary, V Mishra, A Goswami… - Artificial Intelligence …, 2020 - Springer
In recent years, machine learning (ML) and deep learning (DL) have shown remarkable
improvement in computer vision, natural language processing, stock prediction, forecasting …
improvement in computer vision, natural language processing, stock prediction, forecasting …
Lora: Low-rank adaptation of large language models
An important paradigm of natural language processing consists of large-scale pre-training
on general domain data and adaptation to particular tasks or domains. As we pre-train larger …
on general domain data and adaptation to particular tasks or domains. As we pre-train larger …
Ecapa-tdnn: Emphasized channel attention, propagation and aggregation in tdnn based speaker verification
Current speaker verification techniques rely on a neural network to extract speaker
representations. The successful x-vector architecture is a Time Delay Neural Network …
representations. The successful x-vector architecture is a Time Delay Neural Network …
A survey on model compression for large language models
Large Language Models (LLMs) have revolutionized natural language processing tasks with
remarkable success. However, their formidable size and computational demands present …
remarkable success. However, their formidable size and computational demands present …
Wenetspeech: A 10000+ hours multi-domain mandarin corpus for speech recognition
In this paper, we present WenetSpeech, a multi-domain Mandarin corpus consisting of
10000+ hours high-quality labeled speech, 2400+ hours weakly labeled speech, and about …
10000+ hours high-quality labeled speech, 2400+ hours weakly labeled speech, and about …
CHiME-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings
Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the
6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge …
6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge …
Towards edge computing in intelligent manufacturing: Past, present and future
G Nain, KK Pattanaik, GK Sharma - Journal of Manufacturing Systems, 2022 - Elsevier
Abstract Industry 4.0 (I4. 0) is the fourth industrial revolution and a synonym for intelligent
manufacturing. It drives the convergence of several cutting-edge technologies to provoke …
manufacturing. It drives the convergence of several cutting-edge technologies to provoke …
Jasper: An end-to-end convolutional neural acoustic model
In this paper, we report state-of-the-art results on LibriSpeech among end-to-end speech
recognition models without any external training data. Our model, Jasper, uses only 1D …
recognition models without any external training data. Our model, Jasper, uses only 1D …
TED-LIUM 3: Twice as much data and corpus repartition for experiments on speaker adaptation
In this paper, we present TED-LIUM release 3 corpus (TED-LIUM 3 is available on
https://lium. univ-lemans. fr/ted-lium3/) dedicated to speech recognition in English, which …
https://lium. univ-lemans. fr/ted-lium3/) dedicated to speech recognition in English, which …