Clustering-based Phonetic Projection in Mismatched Crowdsourcing Channels for Low-resourced ASR
Wenda Chen, Mark Hasegawa-Johnson, Nancy Chen, Preethi Jyothi, Lav Varshney
Abstract
Acquiring labeled speech for low-resource languages is a difficult task in the absence of native speakers of the language. One solution to this problem involves collecting speech transcriptions from crowd workers who are foreign or non-native speakers of a given target language. From these mismatched transcriptions, one can derive probabilistic phone transcriptions that are defined over the set of all target language phones using a noisy channel model. This paper extends prior work on deriving probabilistic transcriptions (PTs) from mismatched transcriptions by 1) modelling multilingual channels and 2) introducing a clustering-based phonetic mapping technique to improve the quality of PTs. Mismatched crowdsourcing for multilingual channels has certain properties of projection mapping, e.g., it can be interpreted as a clustering based on singular value decomposition of the segment alignments. To this end, we explore the use of distinctive feature weights, lexical tone confusions, and a two-step clustering algorithm to learn projections of phoneme segments from mismatched multilingual transcriber languages to the target language. We evaluate our techniques using mismatched transcriptions for Cantonese speech acquired from native English and Mandarin speakers. We observe a 5-9% relative reduction in phone error rate for the predicted Cantonese phone transcriptions using our proposed techniques compared with the previous PT method.- Anthology ID:
- W16-3714
- Volume:
- Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Venue:
- WSSANLP
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 133–141
- Language:
- URL:
- https://aclanthology.org/W16-3714
- DOI:
- Cite (ACL):
- Wenda Chen, Mark Hasegawa-Johnson, Nancy Chen, Preethi Jyothi, and Lav Varshney. 2016. Clustering-based Phonetic Projection in Mismatched Crowdsourcing Channels for Low-resourced ASR. In Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016), pages 133–141, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Clustering-based Phonetic Projection in Mismatched Crowdsourcing Channels for Low-resourced ASR (Chen et al., WSSANLP 2016)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/W16-3714.pdf