This Saudi Arabian speech dataset features real-world call center conversations from the BFSI domain. With detailed metadata and accurate transcriptions, it’s designed to power ASR systems, voice AI, and conversational agents.
Category
Unscripted Call Center Conversations
Total Volume
40 Speech Hours
Last updated
June 2025
Number of participants
80
This Saudi Arabian Arabic Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Arabic-speaking customers. Featuring over 40 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.
The dataset contains 40 hours of dual-channel call center recordings between native Saudi Arabian Arabic speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.
This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
These transcriptions are production-ready, making financial domain model training faster and more accurate.
Rich metadata is available for each participant and conversation:
This granularity supports BFSI-specific analytics, sentiment modeling, and dialect-aware ASR training.
This dataset is ideal for a range of BFSI voice AI and NLP applications:
We regularly expand this dataset with fresh call recordings and offer tailored options:
This BFSI domain dataset is commercially licensed and ready for integration into your Arabic ASR, NLP, or conversational AI pipeline.
Call Center Conversational AI
ASR
Chatbot
Language Modelling
TTS
Speech Analytics
Dataset Sample(s)
Contact us to get the samples immediately for this dataset.
Language
Arabic
Language code
ar-sa
Country
Saudi Arabia
Gender Distribution
M:60, F:40
Age Group
18-70 Years
Environment
Silent, Noisy
Bit Depth
16 bit
Format
wav
Sample rate
8khz & 16khz
Channel
Stereo (dual-channel, separated speakers)
Audio file duration
5-15 minutes
Similar to Call Center Conversation Speech Datasets
BFSI call center audio data in Italian.
Call Center Conversational AI
ASR
BFSI call center audio data in Argentine Spanish.
Call Center Conversational AI
ASR
BFSI call center audio data in Vietnamese
Call Center Conversational AI
ASR
BFSI call center audio data in Portuguese (Brazil)
Call Center Conversational AI
ASR
More in Arabic (saudi arabia)
Delivery & Logistics call center audio data in Algerian Arabic.
ASR
Conversational AI
Travel call center audio data in Algerian Arabic.
Call Center Conversational AI
ASR
Telecom call center audio data in Egyptian Arabic.
Call Center Conversational AI
ASR
Real Estate call center audio data in Egyptian Arabic.
Call Center Conversational AI
ASR
Need datasets for a specific AI/ML use case?
Don't worry, we've got you covered! 👍
