# Audio Classification Datasets: AI Datasets Source: https://savrn.com/datasets/tasks/audio-classification Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- SAVRN Model Hub · Datasets by Task # Audio Classification Datasets 6 open-weight audio classification datasets in the SAVRN Model Hub, with Silencio Voice AI, Mandip Goswami and CSY20060325 publishing the most. 6Datasets 4Publishers 4Licenses ## Most Downloaded | Dataset | Publisher | License | Monthly downloads | | --- | --- | --- | --- | | [t2a-daddy](https://savrn.com/datasets/t2a-daddy) | Alosh Denny | apache-2.0 | 3.3k | | [english-accents-speech](https://savrn.com/datasets/english-accents-speech) | Silencio Voice AI | cc-by-nc-4.0 | — | | [spanish-accents-speech](https://savrn.com/datasets/spanish-accents-speech) | Silencio Voice AI | cc-by-nc-4.0 | — | | [french-accents-speech](https://savrn.com/datasets/french-accents-speech) | Silencio Voice AI | cc-by-nc-4.0 | — | | [audio-eval-suite](https://savrn.com/datasets/audio-eval-suite) | Mandip Goswami | cc-by-4.0 | — | | [sjj](https://savrn.com/datasets/sjj) | CSY20060325 | Not stated | — | ## Licenses | License | Datasets | Commercial use | | --- | --- | --- | | cc-by-nc-4.0 | 3 | Not without separate permission | | not stated | 1 | Not stated | | cc-by-4.0 | 1 | Yes | | apache-2.0 | 1 | Yes | ## Who Publishes Them | Publisher | Datasets | | --- | --- | | [Silencio Voice AI](https://savrn.com/model-publishers/silencionetwork) | 3 | | [Mandip Goswami](https://savrn.com/model-publishers/mandipgoswami) | 1 | | [CSY20060325](https://savrn.com/model-publishers/csy20060325) | 1 | | [Alosh Denny](https://savrn.com/model-publishers/aoxo) | 1 | ## All 6 Datasets Dataset · Audio classification ### [t2a-daddy](https://savrn.com/datasets/t2a-daddy) [Alosh Denny](https://savrn.com/model-publishers/aoxo) t2a-daddy Male-voice ASMR corpus for the text2asmr project. Previously published as aoxo/audios3. aoxo/t2a-audios-v1 (the original v1 corpus). Layout path what source audio, 48 kHz AAC, one folder per creator word-level Whisper large-v3 alignment ([] = skipped: near-silent or undecodable) labels/qwen3omni.jsonl non-speech ontology labels for gap clips Publicly accessible apache-2.0 [View dataset](https://savrn.com/datasets/t2a-daddy) Dataset · Audio classification ### [audio-eval-suite](https://savrn.com/datasets/audio-eval-suite) [Mandip Goswami](https://savrn.com/model-publishers/mandipgoswami) A small, standardized audio-robustness evaluation set packaged to drop into eval loops. It pairs fully synthetic, license-clean speech-like probe signals with 300 real-synthetic room impulse responses (RIRs) and a labeled degradation chain (reverberation + additive noise), so you can measure how a model's acoustic predictions hold up as rooms get more reverberant and noisier. Think of it as a quick sanity/robustness check: one line to load, a concrete metric, and ground-truth room acoustics for every clip. Measured ground-truth ranges (from the underlying RIRs): - reverbbin distribution: mild 875, strong 600, clean 25 Sources are synthetic speech-LIKE probe signals, not real speech. Each is… Publicly accessible cc-by-4.0 1K