{"id":1573,"datatype":"1","titleimg":"https://www.nexdata.ai/shujutang/static/image/index/datatang_yuyin_default.webp","type1":"165","type1str":null,"type2":"166","type2str":null,"dataname":"In-Bus Ambient Noise Dataset - 19 Hours of Real-World Audio Recordings","datazy":[{"title":"format","content":"48kHZ, 24bit, wav,dual-channel","desc":"format"},{"title":"Content category","content":"Noise","desc":"Content category"},{"title":"Recording condition","content":"in-bus, bus platform","desc":"Recording condition"},{"title":"Recording device","content":"Tascam DR-07x voice recorder","desc":"Recording device"}],"datatag":"Noise,Voice recorder,Bus,Platform","technologydoc":null,"downurl":null,"datainfo":null,"standard":null,"dataylurl":null,"flag":null,"publishtime":null,"createby":null,"createtime":null,"ext1":null,"samplestoreloc":null,"hosturl":null,"datasize":null,"industryPlan":null,"keyInformation":"","samplePresentation":[{"name":"demo1.wav","url":"https://storage-product.datatang.com/damp/product/samplePresentation_ipad/20250722171513/demo1.wav?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=t4E8EWV3gYk1okntq57emXtQJMw%3D","intro":"","size":3840044,"progress":100,"type":"mp3"},{"name":"demo2.wav","url":"https://storage-product.datatang.com/damp/product/samplePresentation_ipad/20250722171513/demo2.wav?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=tpblbJn%2BdtwF0kJrGJYSL3jun6g%3D","intro":"","size":3840044,"progress":100,"type":"mp3"},{"name":"demo3.wav","url":"https://storage-product.datatang.com/damp/product/samplePresentation_ipad/20250722171513/demo3.wav?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=MgodtcICjPvZUZrTiC2v6WjMxWs%3D","intro":"","size":3840044,"progress":100,"type":"mp3"},{"name":"demo4.wav","url":"https://storage-product.datatang.com/damp/product/samplePresentation_ipad/20250722171513/demo4.wav?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=PoBqqDufn3nNQg1D6oDPajQMNMw%3D","intro":"","size":3840044,"progress":100,"type":"mp3"},{"name":"demo5.wav","url":"https://storage-product.datatang.com/damp/product/samplePresentation_ipad/20250722171513/demo5.wav?Expires=4102415999&OSSAccessKeyId=LTAI5tEBeSWUJiqjXvBMsxEu&Signature=OWKkh1a6CD8K7EP2VQHZ7eVC1y4%3D","intro":"","size":3840044,"progress":100,"type":"mp3"}],"officialSummary":"This dataset contains 19 hours of real-world ambient noise recordings captured in bus environments using the Tascam DR-07x voice recorder. The audio was collected from both in-bus scenes and bus platform areas under various real-life conditions. The dataset reflects authentic public transportation soundscapes including engine hum, passenger chatter, door movement, platform announcements, and other background noises. It is suitable for a wide range of applications such as acoustic scene classification, noise suppression, automatic speech recognition (ASR) in noisy environments, and audio enhancement models. The dataset has been tested and validated by leading AI companies and adheres strictly to global data protection standards including GDPR, CCPA, and PIPL, ensuring compliance and safe use in commercial and research applications.","dataexampl":null,"datakeyword":["bus noise dataset","in-bus ambient sound","public transport audio data","vehicle noise dataset","DR-07x noise recording","transportation ambient sound","real-world noise dataset","speech enhancement noise dataset"],"isDelete":null,"ids":null,"idsList":null,"datasetCode":null,"productStatus":null,"tagTypeEn":"Data Type,Language","tagTypeZh":null,"website":null,"samplePresentationList":null,"datazyList":null,"keyInformationList":null,"dataexamplList":null,"bgimg":null,"datazyScriptList":null,"datakeywordListString":null,"sourceShowPage":"speechRec","dataShowType":"[{\"code\":\"0\",\"language\":\"ZH\"},{\"code\":\"1\",\"language\":\"ZH\"},{\"code\":\"2\",\"language\":\"EN,JP,PT,DE,KO,FR,ES\"},{\"code\":\"3\",\"language\":\"EN\"},{\"code\":\"4\",\"language\":\"JP\"}]","productNameEn":"19 Hours Bus Scene Noise Data","BGimg":"brightSpot_audio","voiceBg":["/shujutang/static/image/comm/audio_bg.webp","/shujutang/static/image/comm/audio_bg2.webp","/shujutang/static/image/comm/audio_bg3.webp","/shujutang/static/image/comm/audio_bg4.webp","/shujutang/static/image/comm/audio_bg5.webp"]}
This dataset contains 19 hours of real-world ambient noise recordings captured in bus environments using the Tascam DR-07x voice recorder. The audio was collected from both in-bus scenes and bus platform areas under various real-life conditions. The dataset reflects authentic public transportation soundscapes including engine hum, passenger chatter, door movement, platform announcements, and other background noises. It is suitable for a wide range of applications such as acoustic scene classification, noise suppression, automatic speech recognition (ASR) in noisy environments, and audio enhancement models. The dataset has been tested and validated by leading AI companies and adheres strictly to global data protection standards including GDPR, CCPA, and PIPL, ensuring compliance and safe use in commercial and research applications.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
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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