whisper-large-v3
by openai
Robust speech recognition trained on 680K hours of multilingual audio
openai/whisper-large-v3mixpeek://transcription@v1/openai_whisper_large_v3Overview
Whisper is a general-purpose speech recognition model trained on a massive dataset of diverse audio. It supports multilingual transcription, translation, and language identification. The large-v3 variant achieves near-human accuracy on many benchmarks.
On Mixpeek, Whisper powers audio transcription for video and audio content, generating timestamped text that enables full-text search across spoken content.
Architecture
Encoder-decoder Transformer with 32 encoder layers and 32 decoder layers. Processes 30-second audio segments as 80-channel log-mel spectrograms. Uses multi-task training format with special tokens for timestamps, language, and task type.
Mixpeek SDK Integration
import { Mixpeek } from "mixpeek";
const mx = new Mixpeek({ apiKey: "API_KEY" });
// Managed: create a collection over a bucket; Mixpeek runs this model's extractor
const collection = await mx.collections.create({
namespace_id: "my-namespace",
collection_name: "my-collection",
source: { type: "bucket", bucket_ids: ["bkt_your_bucket"] },
feature_extractor: {
feature_extractor_name: "audio_transcription",
version: "v1",
parameters: { model_id: "openai/whisper-large-v3" },
},
});Capabilities
- 99+ language transcription and translation
- Word-level timestamps
- Robust to background noise, accents, and domain-specific vocabulary
- Automatic language detection
Use Cases on Mixpeek
Benchmarks
| Dataset | Metric | Score | Source |
|---|---|---|---|
| Fleurs (62 langs) | Avg WER | 10.4% | Radford et al., 2023 — Table 1 |
| LibriSpeech (test-clean) | WER | 2.0% | Radford et al., 2023 — Table 2 |
| Common Voice 15 | Avg WER | 11.7% | Whisper model card |
Performance
1.55B params, supports 99 languages
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Specification
Research Paper
Robust Speech Recognition via Large-Scale Weak Supervision
arxiv.orgBuild a pipeline with whisper-large-v3
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
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