Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages

• URL: http://arxiv.org/abs/2607.23808v1
• Date: Sun, 26 Jul 2026 19:12:39 GMT
• Title: Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages
• Abstract summary: Indic DiarBench is a speaker diarization and ASR benchmark dataset spanning all 22 scheduled languages of India.<n>This corpus comprises approximately 108 hours of natural multi-speaker audio from near-field meetings, far-field recordings, and in-the-wild audios.<n>The dataset captures conversational nuance prevalent in Indian speech, such as English code-mixing, dialectal variation, and frequent speaker overlap.
• Score: 16.175337630361454
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this work, we introduce Indic DiarBench, a speaker diarization and ASR benchmark dataset spanning all 22 scheduled languages of India. This corpus comprises approximately 108 hours of natural multi-speaker audio from near-field meetings, far-field recordings, and in-the-wild audios. All annotations are human-corrected with time-aligned speaker attributed transcriptions. The dataset captures conversational nuance prevalent in Indian speech, such as English code-mixing, dialectal variation, and frequent speaker overlap. To establish a baseline for joint ASR and diarization capabilities we evaluate leading systems including commercial speech APIs and multimodal large language models. Indic DiarBench is released as an open-access resource to advance inclusive, multilingual speech technology research for Indian languages.

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