[{"@type":"PropertyValue","name":"Format","value":"44.1kHz, 16bit, wav, dual-channel;"},{"@type":"PropertyValue","name":"Content category","value":"Noise;"},{"@type":"PropertyValue","name":"Recording condition","value":"Noisy environment, including restaurant, supermarket, subway, road, exhibition hall, bus and street;"},{"@type":"PropertyValue","name":"Recording device","value":"Sony ICD-UX560F voice recorder;"},{"@type":"PropertyValue","name":"Features of annotation","value":"timestamp and type for non-noise."}]
{"id":178,"datatype":"1","titleimg":"https://res.datatang.com/asset/productNew/APY170501037.png?Expires=2007353642&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=jlVLZ%2BUfaIfFz21%2Bj9JgtvH7Ycs%3D","type1":"165","type1str":null,"type2":"166","type2str":null,"dataname":"1,297 Hours Environmental Noise Dataset – Multi-Scenario Real-World Audio by Voice Recorder","datazy":[{"title":"Format","content":"44.1kHz, 16bit, wav, dual-channel;","desc":"Format"},{"title":"Content category","content":"Noise;","desc":"Content category"},{"title":"Recording condition","content":"Noisy environment, including restaurant, supermarket, subway, road, exhibition hall, bus and street;","desc":"Recording condition"},{"title":"Recording device","content":"Sony ICD-UX560F voice recorder;","desc":"Recording device"},{"title":"Features of annotation","content":"timestamp and type for non-noise.","desc":"Features of annotation"}],"datatag":"Environmental noise,Scenario,Voice Recorder","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":["1,297 hours","daily noise scene","using Sony ICD-UX560F recording pen"],"samplePresentation":[{"name":"/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0002_P0001_01.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0002_P0001_01.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=yPr2Suf15T82KCIxoieGiBgdXAQ%3D","intro":"","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0001_P0003_01.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0001_P0003_01.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=TiiL2gCHzD4gR4xwr67%2FOB17I3o%3D","intro":"","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0001_P0007_01.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0001_P0007_01.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=giQSemB9MAmGhZLuUCXtlHGefPY%3D","intro":"","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0005_P0007_01.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0005_P0007_01.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=rtrO4QVMUXG99SKe1gIc9Jo3M%2Fk%3D","intro":"","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0005_P0004_01.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY1705010371695808874819/APY170501037/G0005_P0004_01.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=U0rVJOqO6gtTgN1uw6s79PoZKUs%3D","intro":"","size":0,"progress":100,"type":"mp3"}],"officialSummary":"This dataset contains 1,297 hours of environmental noise recordings collected using voice recorders across diverse real-world scenarios, including subways, supermarkets, restaurants, roads, and more. All recordings are annotated with timestamps and relevant metadata, making the data ideal for training AI models in noise reduction, environmental sound classification, audio preprocessing, and speech enhancement tasks. The dataset has been validated by leading AI companies and complies with global data protection regulations including GDPR, CCPA, and PIPL.","dataexampl":null,"datakeyword":["real-world noise data","voice recorder audio","subway noise dataset","supermarket audio dataset","noise reduction training data","sound classification dataset","AI training audio data"],"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","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 1,297 hours of environmental noise recordings collected using voice recorders across diverse real-world scenarios, including subways, supermarkets, restaurants, roads, and more. All recordings are annotated with timestamps and relevant metadata, making the data ideal for training AI models in noise reduction, environmental sound classification, audio preprocessing, and speech enhancement tasks. The dataset has been validated by leading AI companies and complies with global data protection regulations including GDPR, CCPA, and PIPL.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Format
44.1kHz, 16bit, wav, dual-channel;
Content category
Noise;
Recording condition
Noisy environment, including restaurant, supermarket, subway, road, exhibition hall, bus and street;
Specifications
Sample
Recommended Dataset
