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English (US) Call Center Speech Dataset for Travel
The audio dataset comprises call center conversations for the Travel 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
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About this Off-the-shelf Speech Dataset
Introduction
Welcome to the US English Call Center Speech Dataset for the Travel domain designed to enhance the development of call center speech recognition models specifically for the Travel 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 Travel domain, designed to build robust and accurate customer service speech technology.
•
Speakers:
60 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.
•Booking inquiries and assistance
•Destination information and recommendations
•Assistance with flight delays or cancellations
•Special assistance for passengers with disabilities
•Travel-related health and safety inquiry
•Assistance with lost or delayed baggage, and many more
•Promotional offers and package deals
•Customer satisfaction surveys
•Booking confirmations and updates
•Flight schedule changes and notifications
•Customer feedback collection
•Reminders for passport or visa expiration date, 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 Travel 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 Travel 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 Travel sector.
•
Smart Assistants and Chatbots:
Developing conversational agents and virtual assistants for customer service in the Travel 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 Travel 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 Travel 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 |
|---|---|---|---|---|
| Noise | 0.066 | 0.313 | - | - |
| Speech | 2.192 | 3.192 | Speaker 1 | Hello Futurebee. |
| Speech | 4.137 | 5.227 | Speaker 2 | Hello Futurebee. |
| Speech | 7.891 | 11.480 | Speaker 1 | Hi I am <PII>Michael</PII> With, Futurebee Travel. Whom I speaking with today? |
| Speech | 12.775 | 14.214 | Speaker 2 | Hi this is <PII>Mercedes</PII>. |
| Speech | 15.282 | 16.108 | Speaker 1 | Hi <PII>Mercedes</PII>. |
| Speech | 16.510 | 18.318 | Speaker 1 | [filler] how can I help you today? |
| Speech | 19.673 | 31.902 | Speaker 2 | [filler] I just wanted to reach out to your company because I was planning on going on a little vacation. [filler] I was thinking of going to Thailand but honestly I just don't know how |
| Speech | 32.831 | 36.819 | Speaker 2 | will the time or even the know how to book it myself. |
| Speech | 37.539 | 44.517 | Speaker 2 | So I wanted to find out some of your guys pricing and the services that you offer for [filler] as a travel agency. |
| Noise | 45.505 | 45.673 | - | - |
| Speech | 47.051 | 57.240 | Speaker 1 | Okay well you have called the right place [filler] and we would be ecstatic to help you. [filler] real quick. Do you know where in Chiang Mai you want to [filler] do you, do you know where in |
| Speech | 57.981 | 59.234 | Speaker 1 | Thailand you want to visit? |
| Speech | 61.317 | 66.998 | Speaker 2 | [filler] well I was thinking about maybe one of the like coastal towns but |
| Noise | 67.034 | 67.287 | - | - |
| Speech | 67.709 | 70.328 | Speaker 2 | I heard that the mountains are really |
| Speech | 70.757 | 73.040 | Speaker 2 | under rated and thought that that might be |
| Speech | 73.745 | 81.197 | Speaker 2 | might be a bit different thing than my usual like beach get away to, you know, I go to Mexico sometimes so I thought maybe switch it up a bit. |
| Speech | 82.191 | 83.492 | Speaker 2 | So somehwere with the mountains. |
| Speech | 84.239 | 84.769 | Speaker 1 | Okay. |
| Speech | 85.364 | 94.034 | Speaker 1 | Yeah trying to, trying to branch out. [filler] the reason I actually I said Chiang Mai, as soon as you said Thailand, I thought of Chiang Mai. Chiang Mai is one of my favorite places |
| Speech | 94.504 | 103.450 | Speaker 1 | in all of Thailand. Honestly in all of the world. [filler] so, if you are looking for the mountains, Thailand might be a really, Chiang Mai might be a really good place to go. |
| Speech | 104.099 | 106.498 | Speaker 1 | [filler] do you want me to look up some information on that? |
| Speech | 108.421 | 109.763 | Speaker 2 | Yeah sure go ahead. Very fine. |
| Noise | 110.131 | 110.787 | - | - |
| Speech | 111.558 | 121.625 | Speaker 1 | Okay. So while I am getting a few options for you, [filler] could you help me out just, what is your [filler] what is your address? I want to see what airports you close to. |
| Noise | 123.269 | 123.673 | - | - |
| Speech | 123.703 | 128.593 | Speaker 2 | [filler] well I am living in San Antonio, Texas right now [filler]. |
| Speech | 128.967 | 133.563 | Speaker 2 | So I would probably say the San Antonio airport could be the closest. |
| Speech | 133.895 | 136.752 | Speaker 2 | But I often use the Austin |
| Speech | 137.131 | 138.377 | Speaker 2 | airport as well |
| Speech | 139.063 | 139.830 | Speaker 2 | [filler] |
| Speech | 140.895 | 142.300 | Speaker 2 | and if need be |
| Speech | 142.770 | 147.179 | Speaker 2 | I could even travel to [filler] [noise] to Houston or to Dallas |
| Noise | 144.093 | 144.342 | - | - |
| Speech | 147.877 | 152.197 | Speaker 2 | if that really like made a, made a big impact on the price of flights or something like that. |
| Speech | 150.545 | 150.973 | Speaker 1 | Okay |
| Speech | 154.324 | 160.015 | Speaker 1 | Its very possible it could. So I am glad you are able to tell me that you [filler] have that as an availability.[filler] |
| Speech | 160.497 | 163.149 | Speaker 1 | Do you have a time of year you would like to travel? |
| Speech | 164.407 | 169.111 | Speaker 2 | Well I just, we just entered the new year right? So my [filler] |
| Noise | 169.460 | 169.604 | - | - |
| Speech | 170.087 | 173.533 | Speaker 2 | <initial>PTL</initial> for, for my job just renewed. |
| Speech | 174.306 | 176.877 | Speaker 2 | [filler] I don't really want to use it |
| Speech | 178.117 | 180.425 | Speaker 2 | [noise] I don't really want to use it all at the beginning. |
TRANSCRIPTION
| TIME | TRANSCRIPT |
|---|---|
| 0.066 0.313 | - |
| 2.192 3.192 | Hello Futurebee. |
| 4.137 5.227 | Hello Futurebee. |
| 7.891 11.480 | Hi I am <PII>Michael</PII> With, Futurebee Travel. Whom I speaking with today? |
| 12.775 14.214 | Hi this is <PII>Mercedes</PII>. |
| 15.282 16.108 | Hi <PII>Mercedes</PII>. |
| 16.510 18.318 | [filler] how can I help you today? |
| 19.673 31.902 | [filler] I just wanted to reach out to your company because I was planning on going on a little vacation. [filler] I was thinking of going to Thailand but honestly I just don't know how |
| 32.831 36.819 | will the time or even the know how to book it myself. |
| 37.539 44.517 | So I wanted to find out some of your guys pricing and the services that you offer for [filler] as a travel agency. |
| 45.505 45.673 | - |
| 47.051 57.240 | Okay well you have called the right place [filler] and we would be ecstatic to help you. [filler] real quick. Do you know where in Chiang Mai you want to [filler] do you, do you know where in |
| 57.981 59.234 | Thailand you want to visit? |
| 61.317 66.998 | [filler] well I was thinking about maybe one of the like coastal towns but |
| 67.034 67.287 | - |
| 67.709 70.328 | I heard that the mountains are really |
| 70.757 73.040 | under rated and thought that that might be |
| 73.745 81.197 | might be a bit different thing than my usual like beach get away to, you know, I go to Mexico sometimes so I thought maybe switch it up a bit. |
| 82.191 83.492 | So somehwere with the mountains. |
| 84.239 84.769 | Okay. |
| 85.364 94.034 | Yeah trying to, trying to branch out. [filler] the reason I actually I said Chiang Mai, as soon as you said Thailand, I thought of Chiang Mai. Chiang Mai is one of my favorite places |
| 94.504 103.450 | in all of Thailand. Honestly in all of the world. [filler] so, if you are looking for the mountains, Thailand might be a really, Chiang Mai might be a really good place to go. |
| 104.099 106.498 | [filler] do you want me to look up some information on that? |
| 108.421 109.763 | Yeah sure go ahead. Very fine. |
| 110.131 110.787 | - |
| 111.558 121.625 | Okay. So while I am getting a few options for you, [filler] could you help me out just, what is your [filler] what is your address? I want to see what airports you close to. |
| 123.269 123.673 | - |
| 123.703 128.593 | [filler] well I am living in San Antonio, Texas right now [filler]. |
| 128.967 133.563 | So I would probably say the San Antonio airport could be the closest. |
| 133.895 136.752 | But I often use the Austin |
| 137.131 138.377 | airport as well |
| 139.063 139.830 | [filler] |
| 140.895 142.300 | and if need be |
| 142.770 147.179 | I could even travel to [filler] [noise] to Houston or to Dallas |
| 144.093 144.342 | - |
| 147.877 152.197 | if that really like made a, made a big impact on the price of flights or something like that. |
| 150.545 150.973 | Okay |
| 154.324 160.015 | Its very possible it could. So I am glad you are able to tell me that you [filler] have that as an availability.[filler] |
| 160.497 163.149 | Do you have a time of year you would like to travel? |
| 164.407 169.111 | Well I just, we just entered the new year right? So my [filler] |
| 169.460 169.604 | - |
| 170.087 173.533 | <initial>PTL</initial> for, for my job just renewed. |
| 174.306 176.877 | [filler] I don't really want to use it |
| 178.117 180.425 | [noise] I don't really want to use it all at the beginning. |
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
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