English (Australia) Call Center Speech Dataset for Telecom

The audio dataset includes call center conversations in Telecom, featuring native English speakers from Australia, with detailed metadata and accurate transcriptions.

Category

Unscripted Call Center Conversations

Total Volume

40 Speech Hours

Last updated

July 2023

Number of participants

80

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About this Off-the-shelf Speech Dataset

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What’s Included

Welcome to the English Language Call Center Speech Dataset for the Telecom domain. It is a specialized and comprehensive collection of voice data designed to enhance the development of call center speech recognition models specifically for the Telecom industry.


With high-quality call center audio recordings, detailed metadata, and accurate transcriptions, it empowers researchers and developers to enhance natural language processing, conversational AI, and generative voice AI algorithms in the Telecom domain. Moreover, it facilitates the creation of sophisticated voice assistants and voice bots tailored to the unique linguistic nuances found in the English language spoken in Australia.


Speech Data:

This training dataset comprises 40 hours of call center audio recordings covering various topics and scenarios related to the Telecom domain, to build robust and accurate customer service speech technology.


To curate realistic call center interactions, we collaborated with a diverse network of 80 expert native English speakers from different states/provinces of Australia. This collaborative effort ensures a balanced representation of Australian accents, dialects, and demographics, promoting inclusivity and reducing biases in the dataset.


Each audio recording captures the essence of unscripted and spontaneous conversations between call center agents and customers, with an average duration ranging from 5 to 15 minutes per call. The dataset includes both inbound and outbound calls, covering scenarios such as inquiries, promotional offers, complaints, technical support, and more. Additionally, the dataset contains call center conversations with both positive and negative outcomes, providing a diverse and realistic dataset.


The speech data is available in WAV format with stereo channels, a bit depth of 16 bits, and a sample rate of 8 kHz, ensuring high-quality audio for accurate analysis. The recording environment is generally quiet, without background noise and echo.


Metadata:

In addition to the audio recordings, our dataset provides comprehensive metadata for each participant. This includes the participant’s age, gender, country, state, and dialect. Additionally, it includes metadata like domain, topic, call type, outcome, bit depth, and sample rate for each conversation.


The metadata serves as a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of English language call center speech recognition models for the Telecom domain.


Transcription:

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. The transcriptions capture speaker-wise transcription with time-coded segmentation along with non-speech labels and tags, covering both the agent and customer conversations.


These ready-to-use transcriptions accelerate the development of Telecom call center conversational AI and ASR models for the English language.


Updates and Customization:

We understand the importance of collecting data in various environments to build robust ASR models. Therefore, our call center voice dataset is regularly updated with new audio data captured in diverse real-world conditions.


If you require a custom training dataset with specific environmental conditions, we can accommodate your request. We can provide voice data with customized sample rates ranging from 8kHz to 48kHz, allowing you to fine-tune your models for different audio recording setups. Additionally, we can also customize the transcription following your specific guidelines and requirements, to further support your ASR development process.


License:

This Telecom call center audio dataset is created by FutureBeeAI and is available for commercial use!


Conclusion:

Whether you are training or fine-tuning speech recognition models, advancing NLP algorithms, or building state-of-the-art voice assistants to improve customer experiences in the Telecom sector, our dataset serves as a trusted resource to meet your goals


Use Cases

Use of speech data for Automatic Speech Recognition

ASR

Use of speech data in Conversational AI

Conversational AI

Use of speech data for Chatbot & voicebot creation

Chatbot

Use of speech data in Language Modeling

Language Modelling

Use of speech data in Text-into-speech

TTS

Speech data usecase in Speech Analytics

Speech Analytics

Dataset Sample(s)

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Samples will be available soon!

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Dataset Demographics

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Language

English

Language code

en-au

Country

Australia

Accents

Queensland,...more

Gender Distribution

M:55, F:45

Age Group

18-70

Audio File Details

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Environment

Silent, Noisy

Bit Depth

16 bit

Format

wav

Sample rate

8khz

Channel

Dual separate channel

Audio file duration

5-15 minutes

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