Arabic(Egypt) Unscripted Call Center Telephony speech dataset | 617 Hours | Speech Data
Overview
Arabic(Egypt) Unscripted Call Center Telephony speech dataset | 617 Hours | Speech Data is an audio and text dataset. It covers Arabic. The provider states a volume of 617 hours. Typical applications include speech recognition and speech synthesis (TTS). Relevant sectors: AI & Machine Learning and Education. The listing mentions transcription and timestamps. It is offered as a paid dataset; pricing details are provided on request.
Primary applications
What the listing offers
- Stated volume of 617 hours.
- Listing mentions transcription, timestamps.
Arabic(Egypt) Unscripted Call Center Telephony speech dataset, covers telecom, finance, retail, tourism, car, medical domains, including terms and emotions in call center scenario, mirrors real-world interactions. Transcribed with text content, speaker's ID and other attributes. Our dataset was collected from extensive and diversify speakers, geographicly speaking, enhancing model performance in real and complex tasks. 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. Format 8kHz 16bit, wav, mono channel Recording condition Phone recording system, with low background noise (call center scenario) Recording content Spontaneous inbound and outbound callings in typical domain, such as telecom, finance, retail, tourism, car, medical, etc. Country Egypt(EGY) Language Arabic Features of annotation Transcription text, timestamp, speaker ID, noise, sensitive information; Accuracy Word Accuracy Rate (WAR) 98% (punctuation, sentence symbols, accent and other non-speech labeling are not included in accuracy statistics due to subjectivity) Language(Region) Code : ar-EG
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Arabic Spontaneous Dialogue Smartphone speech dataset.
- Language
- Arabic
- Volume
- 144 h
- Domain
- AI & Machine Learning +1
- Use case
- Speech recognition