Boli: A dataset for understanding stuttering experience and analyzing stuttered speech

There is a growing need for diverse, high-quality stuttered speech data, particularly in the context of Indian languages. This paper introduces Project Boli, a multi-lingual stuttered speech dataset designed to advance scientific understanding and technology development for individuals who stutter, particularly in India. The dataset constitutes (a) anonymized metadata (gender, age, country, mother tongue) and responses to a questionnaire about how stuttering affects their daily lives, (b) captures both read speech (using the Rainbow Passage) and spontaneous speech (through image description tasks) for each participant and (c) includes detailed annotations of five stutter types: blocks, prolongations, interjections, sound repetitions and word repetitions. We present a comprehensive analysis of the dataset, including the data collection procedure, experience summarization of people who stutter, severity assessment of stuttering events and technical validation of the collected data. The dataset is released as an open access to further speech technology development.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10888349
Citations
3
Primary Topic
Stuttering Research and Treatment
Type
article
Field-Weighted Citation Impact
6.92
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article

Boli: A dataset for understanding stuttering experience and analyzing stuttered speech

Pradip K. Das, Neeraj Kumar Sharma, Ashita Batra, Mannas narang
3 citations
Stuttering Research and Treatment
6.92
article

Boli: A dataset for understanding stuttering experience and analyzing stuttered speech

Pradip K. Das, Neeraj Kumar Sharma, Ashita Batra, Mannas narang
article en
3 citations

Abstract

There is a growing need for diverse, high-quality stuttered speech data, particularly in the context of Indian languages. This paper introduces Project Boli, a multi-lingual stuttered speech dataset designed to advance scientific understanding and technology development for individuals who stutter, particularly in India. The dataset constitutes (a) anonymized metadata (gender, age, country, mother tongue) and responses to a questionnaire about how stuttering affects their daily lives, (b) captures both read speech (using the Rainbow Passage) and spontaneous speech (through image description tasks) for each participant and (c) includes detailed annotations of five stutter types: blocks, prolongations, interjections, sound repetitions and word repetitions. We present a comprehensive analysis of the dataset, including the data collection procedure, experience summarization of people who stutter, severity assessment of stuttering events and technical validation of the collected data. The dataset is released as an open access to further speech technology development.

Indian Institute of Technology Guwahati (IN)
Openalex Percentile: Top 4%
Stuttering Research and Treatment
6.92
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Boli: A dataset for understanding stuttering experience and analyzing stuttered speech — Pradip K. Das, Neeraj Kumar Sharma, et al. · (2025) | TGRS Research Map | TGRS