# Whisper

## Docs

- [decode()](https://mintlify.wiki/openai/whisper/api/decode.md): Perform decoding of 30-second audio segment(s)
- [DecodingOptions](https://mintlify.wiki/openai/whisper/api/decoding-options.md): Configuration options for decoding audio segments
- [DecodingResult](https://mintlify.wiki/openai/whisper/api/decoding-result.md): Result object containing decoded text and metadata
- [detect_language()](https://mintlify.wiki/openai/whisper/api/detect-language.md): Detect the spoken language in audio
- [load_audio](https://mintlify.wiki/openai/whisper/api/load-audio.md): Load an audio file and convert to mono waveform with resampling
- [load_model()](https://mintlify.wiki/openai/whisper/api/load-model.md): Load a Whisper ASR model
- [log_mel_spectrogram](https://mintlify.wiki/openai/whisper/api/log-mel-spectrogram.md): Compute log-Mel spectrogram from audio waveform
- [Text Normalizers](https://mintlify.wiki/openai/whisper/api/normalizers.md): Text normalization utilities for preprocessing Whisper transcriptions
- [pad_or_trim](https://mintlify.wiki/openai/whisper/api/pad-or-trim.md): Pad or trim audio array to fixed length
- [Tokenizer](https://mintlify.wiki/openai/whisper/api/tokenizer.md): Tokenization utilities for Whisper models
- [transcribe()](https://mintlify.wiki/openai/whisper/api/transcribe.md): Transcribe an audio file using Whisper
- [Whisper Model](https://mintlify.wiki/openai/whisper/api/whisper-model.md): Core Whisper model class and dimensions
- [Architecture](https://mintlify.wiki/openai/whisper/concepts/architecture.md): Technical details of Whisper's model architecture
- [Supported Languages](https://mintlify.wiki/openai/whisper/concepts/languages.md): Languages supported by Whisper and performance characteristics
- [Model Sizes](https://mintlify.wiki/openai/whisper/concepts/models.md): Available Whisper models and their specifications
- [Overview](https://mintlify.wiki/openai/whisper/concepts/overview.md): Understanding Whisper's approach to speech recognition
- [CLI Usage](https://mintlify.wiki/openai/whisper/guides/cli-usage.md): Use Whisper from the command line for audio transcription and translation
- [Language Detection](https://mintlify.wiki/openai/whisper/guides/language-detection.md): Automatically detect the spoken language in audio files
- [Python API](https://mintlify.wiki/openai/whisper/guides/python-api.md): Use Whisper programmatically in your Python applications
- [Translation](https://mintlify.wiki/openai/whisper/guides/translation.md): Translate speech from any language to English with Whisper
- [Word-Level Timestamps](https://mintlify.wiki/openai/whisper/guides/word-timestamps.md): Extract precise word-level timing information from audio transcriptions
- [Installation](https://mintlify.wiki/openai/whisper/installation.md): Set up Whisper on your system
- [Introduction](https://mintlify.wiki/openai/whisper/introduction.md): Robust speech recognition via large-scale weak supervision
- [Quickstart](https://mintlify.wiki/openai/whisper/quickstart.md): Get started with Whisper in minutes
- [Changelog](https://mintlify.wiki/openai/whisper/resources/changelog.md): Version history and release notes for Whisper
- [Model Card](https://mintlify.wiki/openai/whisper/resources/model-card.md): Detailed information about Whisper models including use cases, training data, limitations, and ethical considerations
- [Performance](https://mintlify.wiki/openai/whisper/resources/performance.md): Performance metrics, speed comparisons, and accuracy tradeoffs for Whisper models
- [Troubleshooting](https://mintlify.wiki/openai/whisper/resources/troubleshooting.md): Common issues and solutions when working with Whisper