Audio
Audio is sound represented as a signal or data that can be recorded, transmitted, processed, or reproduced.
Learn Haskell by Example
Audio data is digital information representing sound through sampled signal values and associated recording parameters.
- How it is used
- Models sound as Haskell values for building a WAV-writing musical synthesizer.
- How deep it goes
- Works from sampling through waveform generation, signal limiting, WAV export, and event-driven oscillators; defers richer filters and modulation.
- Examples
- Demonstrates four 220 Hz waveforms exported as WAV audio and several waveform-and-ADSR oscillator presets.
- What you can do after
- Build it from scratch as sampled mono signals, periodic tones, WAV files, and event-driven oscillators.
AI-Powered Search
Audio is recorded or transmitted sound data, including speech, music, and non-language sounds.
- How it is used
- Positions audio as searchable unstructured data and as one modality in multimodal search.
- How deep it goes
- Defines audio and compares its information content with text, but stops short of explaining audio indexing or retrieval implementation.
- Examples
- Uses spoken words, music, non-language sounds, emotion, tone of voice, overlapping communication, and a modality figure.
- What you can do after
- Evaluate audio as a search modality and distinguish speech content from broader acoustic information.
Data Analysis with LLMs
An audio file is a digital file that stores recorded sound for playback or processing.
- How it is used
- Supports recording, transcribing, translating, summarizing, querying, generating, and playing spoken content.
- How deep it goes
- Covers practical recording, playback, and transcription workflows but does not explain audio encoding or signal-processing internals.
- Examples
- Uses recorded employee meetings, voice input, generated speech, and searchable transcripts as concrete applications.
- What you can do after
- Operate/configure Python audio workflows that record, transcribe, translate, summarize, generate, or play spoken content.
Related concepts
- multimodalused by · A multimodal model is a model that processes, generates, or relates information represented in two or more data modalities, such as text, images, audio, or video.
- Whisperused by · Whisper is a family of OpenAI automatic speech-recognition models that transcribe and translate spoken audio, including multilingual audio.
- videopart of · Video is time-ordered visual data represented as a sequence of image frames, often accompanied by synchronized audio.
- transformersused by · Hugging Face Transformers is an open-source library providing pretrained transformer models, tokenizers, and tools for using and training models across machine-learning tasks.
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