.webp&w=640&q=100)
.webp&w=640&q=100)
.webp&w=640&q=100)
.webp&w=640&q=100)
.webp&w=640&q=100)
.webp&w=640&q=100)
.webp&w=640&q=100)
.webp&w=640&q=100)
We Use Cookies!!!
We use cookies to ensure that we give you the best experience on our website. Read cookies policies.
English (US) Call Center Speech Dataset for BFSI
The audio dataset comprises call center conversations for the BFSI domain, featuring native English speakers from US. It includes speech data, detailed metadata and accurate transcriptions.
Category
Unscripted Call Center Conversations
Total Volume
30 Speech Hours
Last updated
Jun 2024
Number of participants
60
Get this Speech Dataset
.webp&w=3840&q=100)
Download
Request Custom Collection
About this Off-the-shelf Speech Dataset
Introduction
Welcome to the US English Call Center Speech Dataset for the BFSI domain designed to enhance the development of call center speech recognition models specifically for the BFSI industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.
Speech Data
This training dataset comprises 30 Hours of call center audio recordings covering various topics and scenarios related to the BFSI domain, designed to build robust and accurate customer service speech technology.
•
Speakers:
60 People expert native US English speakers from the FutureBeeAI Community.
•
Regions:
Different states/provinces of United States of America, ensuring a balanced representation of US accents, dialects, and demographics.
•
Participant Profile:
Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.
•
Conversation Nature:
Unscripted and spontaneous conversations between call center agents and customers.
•
Call Duration:
Average duration of 5 to 15 minutes per call.
•
Formats:
WAV format with stereo channels, a bit depth of 16 bits, and a sample rate of 8 and 16 kHz.
•
Environment:
Without background noise and without echo.
Topic Diversity
This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.
•Debit Card Block Request
•Home Loan Enquiry
•Transaction Disputes
•Credit Card Billing Dispute
•Account Closure Procedures
•Claim Procedures
•Premium Payments
•Policy Comparison
•Policy Cancellation or Lapse
•Insurance Renewal Options
•Retirement Planning
•Investment Risk Assessment Questionnaires
•Tax-efficient Investment Strategies
•Investment Performance Enquiry, and many more
•Credit Card Offers
•Loan Offers
•Loyalty Program Benefits
•Customer Satisfaction Surveys
•EMI Reminder Call
•Policy Upgrade Offers
•Claim Status Updates
•Policyholder Loyalty Benefits
•Insurance Policyholder Surveys
•Term Life Insurance Offer
•Investment Opportunities
•Retirement Savings Review, and many more
This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.
Transcription
To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:
•
Speaker-wise Segmentation:
Time-coded segments for both agents and customers.
•
Non-Speech Labels:
Tags and labels for non-speech elements.
•
Word Error Rate:
Word error rate is less than 5% thanks to the dual layer of QA.
These ready-to-use transcriptions accelerate the development of the BFSI domain call center conversational AI and ASR models for the US English language.
Metadata
The dataset provides comprehensive metadata for each conversation and participant:
•
Participant Metadata:
Unique identifier, age, gender, country, state, district, accent and dialect.
•
Conversation Metadata:
Domain, topic, call type, outcome/sentiment, bit depth, and sample rate.
This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of US English call center speech recognition models.
Usage and Applications
This dataset can be used for various applications in the fields of speech recognition, natural language processing, and conversational AI, specifically tailored to the BFSI domain. Potential use cases include:
•
Speech Recognition Models:
Training and fine-tuning speech recognition models for US English.
•
Speech Analytics Models:
Building speech analytics models to extract insights, identify patterns, and glean valuable information from customer conversation, enables data-driven decision-making and process optimization within the BFSI sector.
•
Smart Assistants and Chatbots:
Developing conversational agents and virtual assistants for customer service in the BFSI industries.
•
Sentiment Analysis:
Analyzing customer sentiment and improving customer experience based on call center interactions.
•
Generative AI:
Training generative AI models capable of generating human-like responses, summaries, or content tailored to the BFSI domain.
Secure and Ethical Collection
•Our proprietary data collection and transcription platform, “Yugo” was used throughout the process of this dataset creation.
•Throughout the data collection process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.
•The data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants.
•It does not include any personally identifiable information about any participant, which makes the dataset safe to use.
•The dataset does not contain any copyrighted content.
Updates and Customization
Understanding the importance of diverse environments for robust ASR models, our call center voice dataset is regularly updated with new audio data captured in various real-world conditions.
•
Environmental Conditions:
Custom collection in specific environmental conditions upon request.
•
Sample Rates:
Customizable from 8kHz to 48kHz.
•
Transcription Customization:
Tailored to specific guidelines and requirements.
License
This BFSI domain call center audio dataset is created by FutureBeeAI and is available for commercial use.
Use Cases
Call Center Conversational AI
ASR
Chatbot
Language Modelling
TTS
Speech Analytics
Dataset Sample(s)
ATTRIBUTES
| Channel 1 | Channel 2 | Format |
|---|---|---|
| Male(29) | Female(24) | wav, json |
TRANSCRIPTION
| LABEL | START | END | CHANNEL | TRANSCRIPT |
|---|---|---|---|---|
| Speech | 0.324 | 1.149 | Speaker 1 | Hello Futurebee. |
| Speech | 2.823 | 3.774 | Speaker 2 | Hello Futurebee. |
| Speech | 6.524 | 10.448 | Speaker 1 | Hi, my name is <PII>John Adams</PII> and you have reached Futurebee financing. How are you? |
| Speech | 12.874 | 14.285 | Speaker 2 | Hi, I am good. My name is |
| Speech | 14.711 | 16.574 | Speaker 2 | <PII>Cour~ Courtney.</PII> |
| Speech | 17.699 | 22.199 | Speaker 1 | <PII>Courtney</PII> Okay, it is good to meet you, <PII>Courtney</PII>. #Ah how can we help you today? |
| Speech | 24.849 | 33.917 | Speaker 2 | Well, I just inherited a very large sum of money from my aunt who has died. |
| Speech | 34.517 | 35.773 | Speaker 2 | She was a very good person. |
| Speech | 36.148 | 36.989 | Speaker 2 | But anyway |
| Speech | 37.589 | 46.680 | Speaker 2 | #Ah I just inherited the money from her and so I am looking for a financial advisor because I have never had this much money in my bank account |
| Speech | 47.330 | 49.121 | Speaker 2 | and I do not really know what to do with it. |
| Speech | 50.722 | 63.149 | Speaker 1 | I will tell what, you are already a step ahead of most people win or inherit money, most of the time the first thing they want to do is spend it on something big and buy gifts for people they like. |
| Speech | 63.597 | 70.171 | Speaker 1 | #Ah but more often than not there are fees they do not realize that come with that sort of money. |
| Speech | 70.322 | 74.224 | Speaker 1 | #Ah they have told me after few questions find out #Ah what kind of |
| Speech | 74.899 | 84.233 | Speaker 1 | what kind of inheritance it was, #Ah what form it maintained. They might give you some ideas how you (()). |
| Speech | 87.596 | 89.022 | Speaker 2 | Okay sounds good. I am ready. |
| Speech | 88.838 | 95.132 | Speaker 1 | Okay. So the first thing I want to ask is, is this (()) in the form of cash or is this an item? |
| Speech | 97.971 | 105.748 | Speaker 2 | #Ah it is, I guess it would be considered cash like I think like it includes some bond as well. I do not really know that counts as cash. |
| Speech | 107.173 | 114.072 | Speaker 1 | Okay. A lot of, a lot of people have (()) understanding bond, not a common thing people already know about but that is fine, fine. |
| Speech | 114.947 | 118.873 | Speaker 1 | Good to know #Ah and then was it |
| Speech | 119.498 | 126.947 | Speaker 1 | gifted to you whether any clauses on the #Ah on the bill perhaps (()) you needed to send that? |
| Speech | 129.323 | 137.765 | Speaker 2 | #Ah it did say that I could have spend it all like at one time like I am only allowed to spend so much |
| Speech | 138.215 | 139.573 | Speaker 2 | per year. |
| Speech | 140.923 | 150.145 | Speaker 2 | #Ah until it you know possibly runs out but I guess that is what I am avoiding is I want to make sure like, like make the money, make money. Right? |
| Speech | 151.546 | 153.885 | Speaker 1 | Yeah. Yeah that is, that is very wise. That makes sense. |
| Speech | 154.235 | 161.019 | Speaker 1 | We, we can help you do all sorts of things with that. #Ah we will give you certain suggestions like how you can pay off (()) debts, |
| Speech | 161.872 | 167.822 | Speaker 1 | #Ah how much of that is going to belong to the government unfortunately #Ah |
| Speech | 168.322 | 168.572 | Speaker 2 | Hmm |
| Speech | 168.472 | 180.044 | Speaker 1 | how you can invest in property, invest in stock shares, #Ah and your pensions. You can even invest in physical assets, send the money for charity #Ah tax right (()). |
TRANSCRIPTION
| TIME | TRANSCRIPT |
|---|---|
| 0.324 1.149 | Hello Futurebee. |
| 2.823 3.774 | Hello Futurebee. |
| 6.524 10.448 | Hi, my name is <PII>John Adams</PII> and you have reached Futurebee financing. How are you? |
| 12.874 14.285 | Hi, I am good. My name is |
| 14.711 16.574 | <PII>Cour~ Courtney.</PII> |
| 17.699 22.199 | <PII>Courtney</PII> Okay, it is good to meet you, <PII>Courtney</PII>. #Ah how can we help you today? |
| 24.849 33.917 | Well, I just inherited a very large sum of money from my aunt who has died. |
| 34.517 35.773 | She was a very good person. |
| 36.148 36.989 | But anyway |
| 37.589 46.680 | #Ah I just inherited the money from her and so I am looking for a financial advisor because I have never had this much money in my bank account |
| 47.330 49.121 | and I do not really know what to do with it. |
| 50.722 63.149 | I will tell what, you are already a step ahead of most people win or inherit money, most of the time the first thing they want to do is spend it on something big and buy gifts for people they like. |
| 63.597 70.171 | #Ah but more often than not there are fees they do not realize that come with that sort of money. |
| 70.322 74.224 | #Ah they have told me after few questions find out #Ah what kind of |
| 74.899 84.233 | what kind of inheritance it was, #Ah what form it maintained. They might give you some ideas how you (()). |
| 87.596 89.022 | Okay sounds good. I am ready. |
| 88.838 95.132 | Okay. So the first thing I want to ask is, is this (()) in the form of cash or is this an item? |
| 97.971 105.748 | #Ah it is, I guess it would be considered cash like I think like it includes some bond as well. I do not really know that counts as cash. |
| 107.173 114.072 | Okay. A lot of, a lot of people have (()) understanding bond, not a common thing people already know about but that is fine, fine. |
| 114.947 118.873 | Good to know #Ah and then was it |
| 119.498 126.947 | gifted to you whether any clauses on the #Ah on the bill perhaps (()) you needed to send that? |
| 129.323 137.765 | #Ah it did say that I could have spend it all like at one time like I am only allowed to spend so much |
| 138.215 139.573 | per year. |
| 140.923 150.145 | #Ah until it you know possibly runs out but I guess that is what I am avoiding is I want to make sure like, like make the money, make money. Right? |
| 151.546 153.885 | Yeah. Yeah that is, that is very wise. That makes sense. |
| 154.235 161.019 | We, we can help you do all sorts of things with that. #Ah we will give you certain suggestions like how you can pay off (()) debts, |
| 161.872 167.822 | #Ah how much of that is going to belong to the government unfortunately #Ah |
| 168.322 168.572 | Hmm |
| 168.472 180.044 | how you can invest in property, invest in stock shares, #Ah and your pensions. You can even invest in physical assets, send the money for charity #Ah tax right (()). |
Dataset Demographics
Language
English
Language code
en-us
Country
USA
Accents
Arizona,...more
Gender Distribution
M:60, F:40
Age Group
18-70
Audio File Details
Environment
Silent, Noisy
Bit Depth
16 bit
Format
wav
Sample rate
8khz & 16khz
Channel
Stereo
Audio file duration
5-15 minutes
Download Sample Speech Dataset Now!
Explore Audio Data, Metadata and Transcription to get more clarity and hands on experience of this dataset.
Download Free Dataset
Start your AI/ML model creation journey with FutureBeeAI!
Contact Us
