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In-Car Speech Dataset: English (US)
- futurebeeai.com
wavUpdated Aug 1, 2022
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EmailClick to copy linkLink copiedCiteFutureBee AI (2022). In-Car Speech Dataset: English (US) [Dataset]. https://www.futurebeeai.com/dataset/monologue-speech-dataset/in-car-speech-dataset-english-uswavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredUnited StatesDataset funded byFutureBeeAIDescriptionIntroduction
Welcome to the US English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.
Speech Data
This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.
•Participant Diversity:•Speakers: 50+ native English speakers from the FutureBeeAI Community.•Regions: Ensures a balanced representation of United States of America1 accents, dialects, and demographics.•Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.•Recording Nature: Scripted wake word and command type of audio recordings.•Duration: Average duration of 5 to 20 seconds per audio recording.•Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.Dataset Diversity
Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.
•Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.•Different Cars: Data collection was carried out in different types and models of cars.•Different Types of Voice Commands:•Navigational Voice Commands•Mobile Control Voice Commands•Car Control Voice Commands•Multimedia & Entertainment Commands•General, Question Answer, Search Commands•Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.•Morning•Afternoon•Evening•Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:•Noise Level: Silent, Low Noise, Moderate Noise, High Noise•Parking Location: Indoor, Outdoor•Car Windows: Open, Closed•Car AC: On, Off•Car Engine: On, Off•Car Movement: Stationary, MovingMetadata
The dataset provides comprehensive metadata for each audio recording and participant:
•Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.• - F
In-Car Speech Dataset: English (UK)
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). In-Car Speech Dataset: English (UK) [Dataset]. https://www.futurebeeai.com/dataset/monologue-speech-dataset/in-car-speech-dataset-english-britishwavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredUnited KingdomDataset funded byFutureBeeAIDescriptionIntroduction
Welcome to the UK English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.
Speech Data
This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.
•Participant Diversity:•Speakers: 50+ native English speakers from the FutureBeeAI Community.•Regions: Ensures a balanced representation of United Kingdom1 accents, dialects, and demographics.•Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.•Recording Nature: Scripted wake word and command type of audio recordings.•Duration: Average duration of 5 to 20 seconds per audio recording.•Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.Dataset Diversity
Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.
•Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.•Different Cars: Data collection was carried out in different types and models of cars.•Different Types of Voice Commands:•Navigational Voice Commands•Mobile Control Voice Commands•Car Control Voice Commands•Multimedia & Entertainment Commands•General, Question Answer, Search Commands•Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.•Morning•Afternoon•Evening•Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:•Noise Level: Silent, Low Noise, Moderate Noise, High Noise•Parking Location: Indoor, Outdoor•Car Windows: Open, Closed•Car AC: On, Off•Car Engine: On, Off•Car Movement: Stationary, MovingMetadata
The dataset provides comprehensive metadata for each audio recording and participant:
•Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.• - F
In-Car Speech Dataset: English (New Zealand)
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). In-Car Speech Dataset: English (New Zealand) [Dataset]. https://www.futurebeeai.com/dataset/monologue-speech-dataset/in-car-speech-dataset-english-newwavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredNew ZealandDataset funded byFutureBeeAIDescriptionIntroduction
Welcome to the New Zealand English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.
Speech Data
This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.
•Participant Diversity:•Speakers: 50+ native English speakers from the FutureBeeAI Community.•Regions: Ensures a balanced representation of New Zealand1 accents, dialects, and demographics.•Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.•Recording Nature: Scripted wake word and command type of audio recordings.•Duration: Average duration of 5 to 20 seconds per audio recording.•Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.Dataset Diversity
Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.
•Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.•Different Cars: Data collection was carried out in different types and models of cars.•Different Types of Voice Commands:•Navigational Voice Commands•Mobile Control Voice Commands•Car Control Voice Commands•Multimedia & Entertainment Commands•General, Question Answer, Search Commands•Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.•Morning•Afternoon•Evening•Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:•Noise Level: Silent, Low Noise, Moderate Noise, High Noise•Parking Location: Indoor, Outdoor•Car Windows: Open, Closed•Car AC: On, Off•Car Engine: On, Off•Car Movement: Stationary, MovingMetadata
The dataset provides comprehensive metadata for each audio recording and participant:
•Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.• - F
In-Car Speech Dataset: English (Canada)
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). In-Car Speech Dataset: English (Canada) [Dataset]. https://www.futurebeeai.com/dataset/monologue-speech-dataset/in-car-speech-dataset-english-canadawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredCanadaDataset funded byFutureBeeAIDescriptionIntroduction
Welcome to the Canadian English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.
Speech Data
This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.
•Participant Diversity:•Speakers: 50+ native English speakers from the FutureBeeAI Community.•Regions: Ensures a balanced representation of Canada1 accents, dialects, and demographics.•Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.•Recording Nature: Scripted wake word and command type of audio recordings.•Duration: Average duration of 5 to 20 seconds per audio recording.•Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.Dataset Diversity
Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.
•Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.•Different Cars: Data collection was carried out in different types and models of cars.•Different Types of Voice Commands:•Navigational Voice Commands•Mobile Control Voice Commands•Car Control Voice Commands•Multimedia & Entertainment Commands•General, Question Answer, Search Commands•Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.•Morning•Afternoon•Evening•Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:•Noise Level: Silent, Low Noise, Moderate Noise, High Noise•Parking Location: Indoor, Outdoor•Car Windows: Open, Closed•Car AC: On, Off•Car Engine: On, Off•Car Movement: Stationary, MovingMetadata
The dataset provides comprehensive metadata for each audio recording and participant:
•Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.• - F
In-Car Speech Dataset: English (Australia)
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). In-Car Speech Dataset: English (Australia) [Dataset]. https://www.futurebeeai.com/dataset/monologue-speech-dataset/in-car-speech-dataset-english-australiawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredAustraliaDataset funded byFutureBeeAIDescriptionIntroduction
Welcome to the Australian English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.
Speech Data
This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.
•Participant Diversity:•Speakers: 50+ native English speakers from the FutureBeeAI Community.•Regions: Ensures a balanced representation of Australia1 accents, dialects, and demographics.•Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.•Recording Nature: Scripted wake word and command type of audio recordings.•Duration: Average duration of 5 to 20 seconds per audio recording.•Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.Dataset Diversity
Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.
•Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.•Different Cars: Data collection was carried out in different types and models of cars.•Different Types of Voice Commands:•Navigational Voice Commands•Mobile Control Voice Commands•Car Control Voice Commands•Multimedia & Entertainment Commands•General, Question Answer, Search Commands•Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.•Morning•Afternoon•Evening•Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:•Noise Level: Silent, Low Noise, Moderate Noise, High Noise•Parking Location: Indoor, Outdoor•Car Windows: Open, Closed•Car AC: On, Off•Car Engine: On, Off•Car Movement: Stationary, MovingMetadata
The dataset provides comprehensive metadata for each audio recording and participant:
•Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.• 
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Introduction
Welcome to the US English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.
Speech Data
This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.
Dataset Diversity
Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.
Metadata
The dataset provides comprehensive metadata for each audio recording and participant: