Designing an IVR Based Framework for Telephony Speech Data Collection and Transcription in Under-Resourced Languages

Basu, Joyanta; Khan, Soma; Bepari, Milton Samirakshma; Roy, Rajib; Pal, Madhab; Nandi, Sushmita

doi:10.21437/sltu.2018-10

Cited by 4 publications

(2 citation statements)

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“…This corpus contains speech data of some rarely studied Indian languages, such as Angami, Bodo, Khasi, Hrangkhawl, and Sumi. Some of the other sources for availing standard Indian speech data are Speehocean, 11 Indic-TTS, 12 13 There are also developments in open-source corpora, such as Mozilla Common Voice, 14 OpenSLR, 15 with speech data for the Indian languages. In Table 3, we have summarized the key information about the major speech corpora developed for Indian spoken language recognition research.…”

Section: Other Developmentsmentioning

confidence: 99%

“…Open source corpora can be developed for the Indian languages by crowd-sourcing or collecting data from the web. For each language, data should be collected from speakers from diferent regions, genders, age groups, and sections of the society [14]. Variations in terms of background noise, recording channels, and room environments should be maintained [70].…”

Section: Issue Of Low-resourcementioning

confidence: 99%

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An Overview of Indian Spoken Language Recognition from Machine Learning Perspective

Dey

Sahidullah

Saha

2022

ACM Trans. Asian Low-Resour. Lang. Inf. Process.

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Automatic spoken language identification (LID) is a very important research field in the era of multilingual voice-command-based human-computer interaction (HCI). A front-end LID module helps to improve the performance of many speech-based applications in the multilingual scenario. India is a populous country with diverse cultures and languages. The majority of the Indian population needs to use their respective native languages for verbal interaction with machines. Therefore, the development of efficient Indian spoken language recognition systems is useful for adapting smart technologies in every section of Indian society. The field of Indian LID has started gaining momentum in the last two decades, mainly due to the development of several standard multilingual speech corpora for the Indian languages. Even though significant research progress has already been made in this field, to the best of our knowledge, there are not many attempts to analytically review them collectively. In this work, we have conducted one of the very first attempts to present a comprehensive review of the Indian spoken language recognition research field. In-depth analysis has been presented to emphasize the unique challenges of low-resource and mutual influences for developing LID systems in the Indian contexts. Several essential aspects of the Indian LID research, such as the detailed description of the available speech corpora, the major research contributions, including the earlier attempts based on statistical modeling to the recent approaches based on different neural network architectures, and the future research trends are discussed. This review work will help assess the state of the present Indian LID research by any active researcher or any research enthusiasts from related fields.

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Section: Other Developmentsmentioning

confidence: 99%

Section: Issue Of Low-resourcementioning

confidence: 99%