[{"@type":"PropertyValue","name":"Format","value":"16k Hz, 16 bit, wav, mono channel"},{"@type":"PropertyValue","name":"Content category","value":"Covering various financial professional terminologies, primarily focuses on macroeconomics(market trends, financial policies, etc.), microeconomics(individual enterprises, stocks, investment portfolios, etc.)"},{"@type":"PropertyValue","name":"Recording condition","value":"Low background noise"},{"@type":"PropertyValue","name":"Country","value":"Italy(ITA)"},{"@type":"PropertyValue","name":"Language(Region) Code","value":"it-IT"},{"@type":"PropertyValue","name":"Language","value":"Italian"},{"@type":"PropertyValue","name":"Features of annotation","value":"transcription text, timestamp, speaker identification, gender, noise, PII redacted, entities, letter case"},{"@type":"PropertyValue","name":"Accuracy","value":"Word Accuracy Rate (WAR) at least 98%"}]
{"id":1541,"datatype":"1","titleimg":"https://www.nexdata.ai/shujutang/static/image/index/datatang_yuyin_default.webp","type1":"165","type1str":null,"type2":"166","type2str":null,"dataname":"200 Hours Italian Financial Speech Dataset – Entity-Annotated Conversations for ASR & AI Training","datazy":[{"title":"Format","content":"16k Hz, 16 bit, wav, mono channel"},{"title":"Content category","content":"Covering various financial professional terminologies, primarily focuses on macroeconomics(market trends, financial policies, etc.), microeconomics(individual enterprises, stocks, investment portfolios, etc.)"},{"title":"Recording condition","content":"Low background noise"},{"title":"Country","content":"Italy(ITA)"},{"title":"Language(Region) Code","content":"it-IT"},{"title":"Language","content":"Italian"},{"title":"Features of annotation","content":"transcription text, timestamp, speaker identification, gender, noise, PII redacted, entities, letter case"},{"title":"Accuracy","content":"Word Accuracy Rate (WAR) at least 98%"}],"datatag":"Italian,Entity,Spontaneous Dialogue,Financial","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":null,"samplePresentation":[{"name":"/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_4.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_4.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=mcY9uCRjzFrthuU0Y7KV%2FFmSsJc%3D","intro":"la piattaforma di crowdfunding, e invece ho detto, aspetta, forse ho sbagliato finestra, ecco.","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_2.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_2.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=qskvX9yq%2FTF2NllEU9hk2m%2FjhoE%3D","intro":"che io faccio tanti collegamenti e pensavo, cazzo ma non mi ricordavo di avere un cantante,","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_7.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_7.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=cMhFDO%2BItiOkihLYs%2B0bgnRaM%2B8%3D","intro":"Ma tu sei, no, invece è molto professional, ma sei batterista?","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_11.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_11.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=pN4LTaUp49RAQ8%2FL3iEpVSbmTwo%3D","intro":"[OVERLAP/]Fonoassorbenti,[/OVERLAP] sì. [OVERLAP/]Questi servono[/OVERLAP] però soltanto soltanto ad assorbire il riverbero interno,","size":0,"progress":100,"type":"mp3"},{"name":"/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_1.wav","url":"https://bj-oss-datatang-03.oss-cn-beijing.aliyuncs.com/filesInfoUpload/data/apps/damp/temp/ziptemp/APY240709005_demo1728468012932/APY240709005_demo/category/013101_1.wav?Expires=4102329599&OSSAccessKeyId=LTAI8NWs2pDolLNH&Signature=evHPcIRygS%2FLU3jvcdd7Xpv8W7E%3D","intro":"E live. Eccolo. Dario, pensavo per un attimo di aver sbagliato collegamento, perché sai","size":0,"progress":100,"type":"mp3"}],"officialSummary":"200 hours of Italian financial speech dataset featuring real-world conversations and monologue recordings enriched with financial entity annotations. The dataset covering various financial professional terminologies, primarily focuses on macroeconomics and microeconomics, mirrors real-world interactions.The data includes transcribed text, speaker ID, gender, generic entities, and other attributes. Our dataset is collected from speakers across a wide geographical area and diverse backgrounds, thus improving the model's performance on real-world, complex tasks. This dataset has passed quality tests by multiple 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":["italian financial speech dataset","financial speech dataset","italian financial ASR dataset","financial conversation dataset","financial speech recognition dataset","financial entity dataset","banking speech 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,PT,DE,KO,FR,ES\"},{\"code\":\"3\",\"language\":\"EN\"},{\"code\":\"4\",\"language\":\"JP\"}]","productNameEn":"200 Hours - Italy(Italian) Financial Entities Real-world Casual Conversation and Monologue speech dataset","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"]}
200 Hours Italian Financial Speech Dataset – Entity-Annotated Conversations for ASR & AI Training
italian financial speech dataset
financial speech dataset
italian financial ASR dataset
financial conversation dataset
financial speech recognition dataset
financial entity dataset
banking speech dataset
200 hours of Italian financial speech dataset featuring real-world conversations and monologue recordings enriched with financial entity annotations. The dataset covering various financial professional terminologies, primarily focuses on macroeconomics and microeconomics, mirrors real-world interactions.The data includes transcribed text, speaker ID, gender, generic entities, and other attributes. Our dataset is collected from speakers across a wide geographical area and diverse backgrounds, thus improving the model's performance on real-world, complex tasks. This dataset has passed quality tests by multiple 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 datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
Specifications
Format
16k Hz, 16 bit, wav, mono channel
Content category
Covering various financial professional terminologies, primarily focuses on macroeconomics(market trends, financial policies, etc.), microeconomics(individual enterprises, stocks, investment portfolios, etc.)
Recording condition
Low background noise
Country
Italy(ITA)
Language(Region) Code
it-IT
Language
Italian
Features of annotation
transcription text, timestamp, speaker identification, gender, noise, PII redacted, entities, letter case
Accuracy
Word Accuracy Rate (WAR) at least 98%
Sample
Audio
la piattaforma di crowdfunding, e invece ho detto, aspetta, forse ho sbagliato finestra, ecco.
Audio
che io faccio tanti collegamenti e pensavo, cazzo ma non mi ricordavo di avere un cantante,
Audio
Ma tu sei, no, invece è molto professional, ma sei batterista?
Audio
[OVERLAP/]Fonoassorbenti,[/OVERLAP] sì. [OVERLAP/]Questi servono[/OVERLAP] però soltanto soltanto ad assorbire il riverbero interno,
Audio
E live. Eccolo. Dario, pensavo per un attimo di aver sbagliato collegamento, perché sai