What is Speech Data?
Speech data is a collection of recorded spoken language used to train machine learning models for various applications. It includes audio recordings, transcriptions, phonetic annotations, and other linguistic data. Examples of speech data include voice command data, multilingual speech data, and annotated conversational recordings. This data is essential for developing speech recognition systems, natural language processing (NLP) tools, and enhancing human-computer interactions. On this page, you’ll find the best data sources for various types of speech data.
Best Speech Datasets & APIs
Nexdata | Multilingual Code-switching Speech Data | 5,000 Hours |Audio Data| Speech Recognition Data|AI Training Data
WebAutomation Off the Shelf Datasets | Audio Data for AI & ML Training | 600+ Hours of Recording | Speech Recognition, Natural Language Processing
Way With Words' Afrikaans Speech Collection Dataset
Deeply Korean Read Speech Corpus - Audio AI & ML Training Data
Bulgarian audio dataset for speech recognition 10 hours (4/4)
Nexdata | Speech Recognition Data Collection Services | 100+ Languages Resources |Audio Data | Speech Recognition Data | Machine Learning (ML) Data
Way With Words' seSotho Speech Collection Dataset
Bulgarian audio dataset for speech recognition 20 hours (3/4)
Nexdata | Multilingual Read Speech Data | 65,000 Hours | Generative AI Audio Data| Speech Recognition Data | Machine Learning (ML) Data
Monetize data on Datarade Marketplace
What Type of Data is Speech Data?
Types of speech data include:
- Voice Commands: Short phrases or commands used for activating devices or services.
- Conversational Speech: Natural dialogue recordings used for training dialogue systems.
- Multilingual Speech: Recordings in multiple languages for developing multilingual AI systems.
What is the Bit Rate of Speech Data?
The bit rate of speech, or data rate, indicates the amount of data processed per unit of time in an audio file. Common speech data rates are:
- 8 kbps: Typically used in telephony for low-quality speech.
- 16 kbps: Standard for narrowband speech coding.
- 64 kbps: High-quality speech, often used in digital voice recordings.
How is Speech Data Collected?
Speech data can be collected through various methods:
- Field Recordings: Capturing natural conversations in real-world environments.
- Studio Recordings: Using controlled settings to record clear and high-quality audio.
- Crowdsourcing: Gathering data from volunteers who provide speech samples.
- Existing Databases: Utilizing publicly available speech datasets from research institutions.
What is Voice Data?
Voice data, spoken data and speech data essentially mean the same thing. They all refer to audio recordings where human language is articulated. This can include everyday conversations, interviews, public speeches, and scripted dialogues. These terms are used interchangeably in fields like Natural Language Processing (NLP) and speech-to-text technologies to describe the raw audio input that is analyzed and processed to develop and improve various applications.
Why is Speech Data Important for AI?
Speech data is crucial for AI technologies, particularly in the fields of speech recognition and NLP. It allows AI systems to understand and process human language, making interactions more natural and intuitive. Integrating speech data with other types of AI training data, such as textual data and Deep Learning Data, enhances the performance of AI models.