TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baseline
This paper introduces a new corpus of Mandarin-English code-switching speech recognition--TALCS corpus, suitable for training and evaluating code-switching speech recognition systems. TALCS corpus is derived from real online one-to-one English teaching scenes in TAL education group, which contains roughly 587 hours of speech sampled at 16 kHz. To our best knowledge, TALCS corpus is the largest well labeled Mandarin-English code-switching open source automatic speech recognition (ASR) dataset in the world. In this paper, we will introduce the recording procedure in detail, including audio capturing devices and corpus environments. And the TALCS corpus is freely available for download under the permissive license1. Using TALCS corpus, we conduct ASR experiments in two popular speech recognition toolkits to make a baseline system, including ESPnet and Wenet. The Mixture Error Rate (MER) performance in the two speech recognition toolkits is compared in TALCS corpus. The experimental results implies that the quality of audio recordings and transcriptions are promising and the baseline system is workable.
Code (0)
등록된 구현이 없습니다.
Tasks
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speech-recognitionSpeech RecognitionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Introducing MELI: the Mandarin-English Language Interview Corpus
We introduce the Mandarin-English Language Interview (MELI) Corpus, an open-source resource of 29.8 hours of speech from 51 Mandarin-English bilingual speakers. MELI combines matched sessions in Mandarin and English with…
The ASRU 2019 Mandarin-English Code-Switching Speech Recognition Challenge: Open Datasets, Tracks, Methods and Results
Code-switching (CS) is a common phenomenon and recognizing CS speech is challenging. But CS speech data is scarce and there' s no common testbed in relevant research. This paper describes the design and main outcomes of …
Data AugmentationLanguage Identificationspeech-recognitionSpeech RecognitionTaiwanese-Accented Mandarin and English Multi-Speaker Talking-Face Synthesis System
This paper proposes a multi-speaker talking-face synthesis system. The system incorporates voice cloning and lip-syncing technology to achieve text-to-talking-face generation by acquiring audio and video clips of any spe…
Face GenerationSpeech SynthesisTalking Face GenerationTransfer Learning+1Exploiting Low-Resource Code-Switching Data to Mandarin-English Speech Recognition Systems
In this paper, we investigate how to use limited code-switching data to implement a code-switching speech recognition system. We utilize the Transformer end-to-end model to develop our code switching speech recognition s…
Language ModelingLanguage ModellingMulti-Task Learningspeech-recognition+2Monolingual Data Selection Analysis for English-Mandarin Hybrid Code-switching Speech Recognition
In this paper, we conduct data selection analysis in building an English-Mandarin code-switching (CS) speech recognition (CSSR) system, which is aimed for a real CSSR contest in China. The overall training sets have thre…
speech-recognitionSpeech Recognition