What is Audio Data?
Audio data is a collection of sound recordings used by different technologies for various applications. It consists of digital recordings such as human voice, music, environmental sounds, and other auditory data. Examples of audio data include speech data, sound classification samples, and audio annotations. This data is crucial for developing machine learning models, generative AI, and speech recognition systems. On this page, youâll find the best data sources for various types of audio data.
Best Audio Datasets & APIs
Nexdata | Multilingual Speech Synthesis Data | 400 Hours | TTS Data | Audio Data | AI Training Data
TagX Data collection for AI/ ML training | LLM data | Data collection for AI development & model finetuning | Text, image, audio, and document data
WebAutomation Off the Shelf Datasets | Audio Data for AI & ML Training | 600+ Hours of Recording | Speech Recognition, Natural Language Processing
Shaip - Multilingual Conversational AI Training Data (Text & Audio)
Bulgarian audio dataset for speech recognition 10 hours (4/4)
AI-Machine Learning Sound / Audio / Snippet Recordings Database
Deeply Korean Read Speech Corpus - Audio AI & ML Training Data
US Public Companies Earning Calls Audio and Video Database - FactSquared Transcribe
Data Collection by EPIC Translations: Copywriting, Text & Audio Data Data for AI & ML Training
Monetize data on Datarade Marketplace
What are Examples of Audio Data?
AI training data is crucial for the development of machine learning models. Audio data, in particular, is used to train systems for a variety of applications. These are the main examples of audio data:
- Music Files: Music files used for sound classification.
- Speech Recordings: Interviews, podcasts, and dialogues used in speech recognition systems.
- Environment Samples: Ambient sounds, sound effects, and synthesized sounds used in multimedia.
- Audiovisual Content: Audio tracks from movies, TV shows, radio broadcasts, and video games.
- Voice Assistants: Voice commands and responses used by AI systems like Siri, Alexa, and Google Assistant.
- Phone Call Recordings: Customer service calls, earning calls, and any other calls recorded for analysis.
What are the Types of Audio Data?
Audio data is primarily stored in digital formats such as WAV, MP3, and FLAC. These formats encode sound waves into a digital form that computers can process. Audio data can be found in 3 main formats:
Uncompressed Audio Data
- PCM, WAV, AIFF: High-quality, raw audio ideal for tasks needing fidelity, like speech recognition.
Lossless Compressed Audio Data
- FLAC, ALAC, WavPack: Maintains high quality with reduced file size, suitable for high-fidelity audio training.
Lossy Compressed Audio Data
- MP3, AAC, OGG Vorbis, WMA: Efficient for storage and bandwidth, useful for general audio tasks with some quality loss.
How Can You Utilize Audio Data?
Audio data can be utilized in multiple ways, particularly in the development of AI applications:
- Speech Recognition: Converting spoken language into text, enabling functionalities like voice search and transcription.
- Natural Language Processing (NLP): Enhancing the ability of machines to understand and respond to human language.
- Voice Assistants: Powering AI assistants like Siri, Alexa, and Google Assistant to respond to voice commands.
- Music and Sound Analysis: Analyzing audio to identify patterns, genres, or even to recommend new music.
- Security Systems: Using audio for surveillance and identification purposes, such as voice biometrics.