VoiceArena/MonsoonASR-Open-ASR-leaderboard-en-IN

Voice Arena Monsoon en-IN (public test)

Part of the Open ASR Leaderboard, in the main board's default column set, so it contributes to the headline Average WER for every model listed.

A conversational Indian English ASR test set that records who was speaking, not only what was said. Every clip carries twelve speaker attributes — gender, age, native district and state, education, occupation, income band, handset — so a difference between two systems can be traced to a group of speakers instead of disappearing into one number.

This is the public split, released for self-scoring. A speaker-disjoint private split is withheld to limit benchmark-specific optimisation.

At a glance

Clips	2,102
Duration	5.62 h
Speakers	1,444
Clip length	9.6 s mean / 10.4 s median
Male / female clips	50 / 50
Native districts	428
States / UTs	24 states + 6 union territories
Distinct handset models	556
Current cities	641

Small in hours, large in speakers: more than half the speakers contribute exactly one clip, and the ten largest contributors account for under 7 per cent of total duration. A result here is an average over hundreds of voices rather than a few talkers recorded at length.

Loading

from datasets import load_dataset

ds = load_dataset("VoiceArena/MonsoonASR-Open-ASR-leaderboard-en-IN", split="test")
print(ds[0]["text"], ds[0]["native_district"], ds[0]["gender"])

Audio is 16 kHz.

Scoring

Reference transcripts are plain strings. Score with word error rate after the Open ASR Leaderboard normaliser, and report the aggregate over the split — sum(ins + del + sub) / sum(reference words) — not the average of per-clip rates.

Fields

Group	Fields
Segment	id, audio, audio_length_s, language
Reference	text
Speaker	speaker_id, gender, date_of_birth
Background	occupation, educational_background, marital_status, income
Geography	native_district, native_state, current_city, years_spent_in_current_district
Recording	device_manufacturer, device_model

More

Collection, quality control, the transcription protocol and a worked regional analysis: https://huggingface.co/blog/open-asr-leaderboard-global-south.