Unsupervised cross-lingual representation learning for speech recognition
This paper presents XLSR which learns cross-lingual speech representations by pretraining
a single model from the raw waveform of speech in multiple languages. We build on …
a single model from the raw waveform of speech in multiple languages. We build on …
Automatic speech recognition for under-resourced languages: A survey
Speech processing for under-resourced languages is an active field of research, which has
experienced significant progress during the past decade. We propose, in this paper, a …
experienced significant progress during the past decade. We propose, in this paper, a …
Frontier Research on Low-Resource Speech Recognition Technology
W Slam, Y Li, N Urouvas - Sensors, 2023 - mdpi.com
With the development of continuous speech recognition technology, users have put forward
higher requirements in terms of speech recognition accuracy. Low-resource speech …
higher requirements in terms of speech recognition accuracy. Low-resource speech …
Multitask learning of deep neural networks for low-resource speech recognition
D Chen, BKW Mak - IEEE/ACM Transactions on Audio, Speech …, 2015 - ieeexplore.ieee.org
We propose a multitask learning (MTL) approach to improve low-resource automatic speech
recognition using deep neural networks (DNNs) without requiring additional language …
recognition using deep neural networks (DNNs) without requiring additional language …
Crossing the conversational chasm: A primer on natural language processing for multilingual task-oriented dialogue systems
In task-oriented dialogue (ToD), a user holds a conversation with an artificial agent with the
aim of completing a concrete task. Although this technology represents one of the central …
aim of completing a concrete task. Although this technology represents one of the central …
Automatic speech recognition system for tonal languages: State-of-the-art survey
Natural language and human–machine interaction is a very much traversed as well as
challenging research domain. However, the main objective is of getting the system that can …
challenging research domain. However, the main objective is of getting the system that can …
Evaluating phonemic transcription of low-resource tonal languages for language documentation
Transcribing speech is an important part of language documentation, yet speech recognition
technology has not been widely harnessed to aid linguists. We explore the use of a neural …
technology has not been widely harnessed to aid linguists. We explore the use of a neural …
End-to-end speech recognition for arabic dialects
Automatic speech recognition or speech-to-text is a human–machine interaction task, and
although it is challenging, it is attracting several researchers and companies such as …
although it is challenging, it is attracting several researchers and companies such as …
Transfer ability of monolingual wav2vec2. 0 for low-resource speech recognition
C Yi, J Wang, N Cheng, S Zhou… - 2021 international joint …, 2021 - ieeexplore.ieee.org
Recently, there are several domains that have their own feature extractors, such as ResNet,
BERT, and GPT-x, which are widely used for various down-stream tasks. These models are …
BERT, and GPT-x, which are widely used for various down-stream tasks. These models are …
Joint acoustic modeling of triphones and trigraphemes by multi-task learning deep neural networks for low-resource speech recognition
It is well-known in machine learning that multitask learning (MTL) can help improve the
generalization performance of singly learning tasks if the tasks being trained in parallel are …
generalization performance of singly learning tasks if the tasks being trained in parallel are …