datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
voice-code-bench
VoiceCodeBench
VoiceCodeBench is a test-only benchmark for evaluating whether automatic
speech recognition (ASR) systems preserve exact structured values in English
workplace speech.
Paper: VoiceCodeBench: Evaluating Exact Structured-Token Recovery in Automatic Speech Recognition
The benchmark targets cases where a transcript is software input: callback
numbers, email addresses, command-line flags, file paths, URLs, account
identifiers, dates, measurements, and similar values… See the full description on the dataset page: https://huggingface.co/datasets/besimple-ai/voice-code-bench.voice-code-bench
VoiceCodeBench
VoiceCodeBench is a test-only benchmark for evaluating whether automatic
speech recognition (ASR) systems preserve exact structured values in English
workplace speech.
Paper: VoiceCodeBench: Evaluating Exact Structured-Token Recovery in Automatic Speech Recognition
The benchmark targets cases where a transcript is software input: callback
numbers, email addresses, command-line flags, file paths, URLs, account
identifiers, dates, measurements, and similar values… See the full description on the dataset page: https://huggingface.co/datasets/yunqi1766/voice-code-bench.codeswitch-pairs-lase
Codeswitch Pairs LASE — training corpus
1118 same-voice cross-script utterance pairs (8 ElevenLabs Multilingual voices × en/hi/te/ta) used to train the LASE r1 speaker encoder.
Each row is one synthesized utterance with metadata; pairs are reconstructed at evaluation time by joining on voice_id (same voice, different script = cross-script pair).
Schema (manifest.jsonl)
{
"voice_id": "21m00Tcm4TlvDq8ikWAM",
"lang": "en | hi | te | ta",
"text": "the prompt text"… See the full description on the dataset page: https://huggingface.co/datasets/Praxel/codeswitch-pairs-lase.