[{"@type":"PropertyValue","name":"Format","value":"16kHz, 16bit, uncompressed wav, mono channel;"},{"@type":"PropertyValue","name":"Recording condition","value":"Low background noise(indoor), without echo;"},{"@type":"PropertyValue","name":"Content category","value":"Generic domain; human-machine interaction; smart home command and control; in-car command and control; numbers;"},{"@type":"PropertyValue","name":"Recording device","value":"Android Smartphone, iPhone;"},{"@type":"PropertyValue","name":"Speaker","value":"2,100 speakers totally, with 52% male and 48% female; and 81% speakers of all are in the age group of 18-25,18% speakers of all are in the age group of 26-45, 1% speakers of all are in the age group of 46-60;"},{"@type":"PropertyValue","name":"Country","value":"India(IND);"},{"@type":"PropertyValue","name":"Language(Region) Code","value":"en-IN;"},{"@type":"PropertyValue","name":"Language","value":"English;"},{"@type":"PropertyValue","name":"Features of annotation","value":"Transcription text;"},{"@type":"PropertyValue","name":"Accuracy Rate","value":"Sentence Accuracy Rate (SAR) 95%"}]
{"id":940,"datatype":"1","titleimg":"https://res.datatang.com/asset/productNew/APY181231003.png?Expires=2007353651&OSSAccessKeyId=LTAI5tQwXnJZbubgVfVa1ep9&Signature=9L5fp11sWl4VVJZ2zpAWbOi2wK8%3D","type1":"165","type1str":null,"type2":"166","type2str":null,"dataname":"Indian English Speech Dataset (1,012 Hours) with Transcripts for ASR & Voice AI","datazy":[{"title":"Format","content":"16kHz, 16bit, uncompressed wav, mono channel;","desc":"Format"},{"title":"Recording condition","content":"Low background noise(indoor), without echo;","desc":"Recording condition"},{"title":"Content category","content":"Generic domain; human-machine interaction; smart home command and control; in-car command and control; numbers;","desc":"Content category"},{"title":"Recording device","content":"Android Smartphone, iPhone;","desc":"Recording device"},{"title":"Speaker","content":"2,100 speakers totally, with 52% male and 48% female; and 81% speakers of all are in the age group of 18-25,18% speakers of all are in the age group of 26-45, 1% speakers of all are in the age group of 46-60;","desc":"Speaker"},{"title":"Country","content":"India(IND);","desc":"Country"},{"title":"Language(Region) Code","content":"en-IN;","desc":"Language(Region) Code"},{"title":"Language","content":"English;","desc":"Language"},{"title":"Features of annotation","content":"Transcription text;","desc":"Features of annotation"},{"title":"Accuracy Rate","content":"Sentence Accuracy Rate (SAR) 95%","desc":"Accuracy Rate"}],"datatag":"English,India,Mobile Phone,Reading,Scripted Monologue","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":["1012 hours","2100 speakers","balanced in gender and age"],"samplePresentation":[{"name":"/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0650S3361.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0650S3361.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=FWvuKxLsyJUeylS7DwEQzBm2f40%3D","intro":"Play that song again and again","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G00849S4374.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G00849S4374.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=e0gipejHmh0ktFx1MT2eWuDDegI%3D","intro":"Repeat The Song Please","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0009S5398.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0009S5398.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=YvYHs6VdKLzbJMmB%2Bg%2FA2EKMiRE%3D","intro":"zero five five one seven eight two five zero one","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0009S1001.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0009S1001.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=jM7eITCDZMROsN0qY2MZtoZLXDo%3D","intro":"After I finish up here, we can talk about your training in Paris.","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0407S2309.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY181231003_demo1695808924681/G0407S2309.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=0F%2Fq6rXdIZjb%2BwQjWOYL%2F3p5ZS4%3D","intro":"Replay the song Still Ain't Bound.","size":0,"progress":100,"type":"mp3"}],"officialSummary":"This Indian English speech dataset contains over 1,000 hours of audio recorded via mobile devices from 2,100 native speakers across India. Collected from monologue based on given scripts, covering generic domain, human-machine interaction, smart home command and in-car command, numbers and other domains. Transcribed with text content and other attributes. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.","dataexampl":null,"datakeyword":["indian english speech dataset","indian accent speech dataset","english india speech dataset","indian english ASR dataset","indian english voice dataset","indian english speech corpus"],"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":"1,012 Hours - Indian English Speech Data by Mobile Phone","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"]}
Indian English Speech Dataset (1,012 Hours) with Transcripts for ASR & Voice AI
indian english speech dataset
indian accent speech dataset
english india speech dataset
indian english ASR dataset
indian english voice dataset
indian english speech corpus
This Indian English speech dataset contains over 1,000 hours of audio recorded via mobile devices from 2,100 native speakers across India. Collected from monologue based on given scripts, covering generic domain, human-machine interaction, smart home command and in-car command, numbers and other domains. Transcribed with text content and other attributes. Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.
This is a paid dataset licensed for commercial use. Ready-made datasets are available for immediate integration into AI projects.
Specifications
Format
16kHz, 16bit, uncompressed wav, mono channel;
Recording condition
Low background noise(indoor), without echo;
Content category
Generic domain; human-machine interaction; smart home command and control; in-car command and control; numbers;
Recording device
Android Smartphone, iPhone;
Speaker
2,100 speakers totally, with 52% male and 48% female; and 81% speakers of all are in the age group of 18-25,18% speakers of all are in the age group of 26-45, 1% speakers of all are in the age group of 46-60;
Country
India(IND);
Language(Region) Code
en-IN;
Language
English;
Features of annotation
Transcription text;
Accuracy Rate
Sentence Accuracy Rate (SAR) 95%
Sample
Audio
Play that song again and again
Audio
Repeat The Song Please
Audio
zero five five one seven eight two five zero one
Audio
After I finish up here, we can talk about your training in Paris.
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.
Specifications
Sample
Recommended Dataset
