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Home > All Category Datasets > Speech Recognition Datasets > In-Car Noise Dataset – 531 Hours of Cabin Recordings

In-Car Noise Dataset – 531 Hours of Cabin Recordings

in-car noise dataset
vehicle interior sound
car ambient noise
automotive audio dataset
cabin noise data
car sound modeling
speech enhancement training data
vehicle noise cancellation dataset

This dataset contains 531 hours of in-car ambient noise recordings captured using microphones and mobile phones across various vehicle models, road types, speeds, and cabin conditions such as windows open or closed. The noise was recorded at six distinct points inside each vehicle to reflect spatial diversity and better support vehicle sound modeling. The dataset captures real-world driving environments, engine hums, road interactions, wind noise, and cabin reverberation. It is ideal for use cases such as noise suppression, automatic speech recognition (ASR) in cars, in-vehicle audio enhancement, and sound source separation. Validated by leading AI companies, the dataset complies fully with global data privacy regulations including GDPR, CCPA, and PIPL, making it suitable for both research and commercial applications.

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SpecificationsSpecifications
Format
microphone 32kHz 32bit,wav mono channel ; mobile phone: 16kHz, 16bit, mono channel
Data Content
contains 5 conditions each category has multiple scenarios each speech has a corresponding scenarios combination
Collection weather
317 hours on sunny days; 214 hours on rainy days
Recording Environment
in-car,10 different models at different prices
Device
recording by 4 microphones and 2 mobile phones simultaneously ,deployed at 6 points in car
Annotation Content
annotation result contaning road type, weather, air conditioning switch and other information
Application Scenario
noise modelling
Sample Sample
  • Audio

    道路类型:停车怠速(0)；天气:晴天；空调开关:关；右前车窗:关闭；右后车窗:关闭；气温:2；拥堵情况:畅通；平均车速:0；车型:轿车别克君威

  • Audio

    道路类型:停车怠速(0)；天气:晴天；空调开关:中；右前车窗:关闭；右后车窗:关闭；气温:1；拥堵情况:正常；平均车速:0；车型:轿车大众捷达

  • Audio

    道路类型:环线辅路(65,±15)；天气:雨天；空调开关:高；右前车窗:关闭；右后车窗:关闭；气温:24；拥堵情况:疏通；平均车速:71；车型:别克昂拉克

  • Audio

    道路类型:环线辅路(65,±15)；天气:晴天；空调开关:关；右前车窗:关闭；右后车窗:关闭；气温:3；拥堵情况:正常；平均车速:65；车型:东风日产奇骏

  • Audio

    道路类型:环线辅路(65,±15)；天气:晴天；空调开关:关；右前车窗:关闭；右后车窗:打开2cm；气温:6；拥堵情况:无拥堵；平均车速:68；车型:丰田雷凌

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What languages and scenarios are covered by Nexdata’s speech recognition datasets?

Nexdata offers speech recognition datasets covering a broad range of languages, dialects, and accents, backed by extensive global language resources. Our datasets include diverse speakers, acoustic environments, and real-world speech scenarios, supporting multilingual ASR, voice assistants, conversational AI, speech-to-text, and other speech-enabled applications.

Can Nexdata customize speech recognition datasets for specific languages or requirements?

Yes. If our off-the-shelf datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, transcription, and annotation services. We can customize datasets based on target languages or dialects, speaker profiles, recording environments, speech scenarios, data volume, and annotation specifications to meet specific ASR development needs.

How does Nexdata ensure the quality and scalability of speech recognition datasets?

Nexdata applies multi-stage quality control throughout speech data collection, transcription, annotation, and validation. Combined with our extensive language resources and scalable collection capabilities, we can support both large-scale multilingual projects and specialized datasets for specific languages, dialects, accents, and speech scenarios.

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