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English (US) Call Center Speech Dataset for Real Estate
The audio dataset comprises call center conversations for the Real Estate 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 Real Estate domain designed to enhance the development of call center speech recognition models specifically for the Real Estate 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 Real Estate 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.
•Property Inquiry
•Rental Property Search & Availability
•Renovation Inquiries
•Property Features & Amenities Inquiry
•Investment Property Analysis & Advice
•Property History & Ownership Details, and many more
•New Property Listing Update
•Post Purchase Follow-ups
•Investment Opportunities & Property Recommendations
•Property Value Updates
•Customer Satisfaction Surveys, 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:
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Speaker-wise Segmentation:
Time-coded segments for both agents and customers.
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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 Real Estate 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 Real Estate 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 Real Estate sector.
•
Smart Assistants and Chatbots:
Developing conversational agents and virtual assistants for customer service in the Real Estate 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 Real Estate 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 Real Estate 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 | 0.185 | 0.920 | - | - |
| Speech | 0.364 | 1.298 | Speaker 1 | Hello Futurebee. |
| Noise | 3.129 | 3.407 | - | - |
| Speech | 3.415 | 4.237 | Speaker 2 | Hello Futurebee. |
| Speech | 5.932 | 10.426 | Speaker 1 | Hi my name is <PII>Kurt Holt</PII>. You reached [filler] the number one tax realtor. |
| Speech | 11.519 | 13.499 | Speaker 1 | [filler] can I (()) this call? |
| Speech | 14.903 | 16.829 | Speaker 2 | Hi this is <PII>Mercedes Holt</PII>. |
| Speech | 18.297 | 26.225 | Speaker 1 | Okay <PII>Mercedes Holt</PII>. Its good to meet you. [filler] we are, we are happy to help you today. May I ask how, how we are able to help? |
| Noise | 22.033 | 22.635 | - | - |
| Speech | 28.370 | 34.429 | Speaker 2 | Yeah [filler] my husband and I are on the market for a brand new beautiful house. |
| Speech | 34.877 | 38.526 | Speaker 2 | In Texas, we just moved here from California. |
| Speech | 39.060 | 39.975 | Speaker 2 | And |
| Speech | 40.359 | 50.990 | Speaker 2 | we are really looking for a nice green house. So we need some help from one of your realtors. [filler] I am calling to ask about pricing, and what kind of packages you guys have because we |
| Speech | 51.523 | 52.966 | Speaker 2 | really are looking for |
| Speech | 53.387 | 55.835 | Speaker 2 | by just a shining star of a realtor to help us. |
| Speech | 57.710 | 71.260 | Speaker 1 | Okay well to be honest I really think you came to the right place. [filler] I have worked for two other real, real estate companies before and I am stuck with this one for ten years because of our (()). I hope we can give you, get you what you need. |
| Noise | 72.063 | 72.266 | - | - |
| Speech | 72.492 | 73.194 | Speaker 1 | [filler] |
| Speech | 73.825 | 74.376 | Speaker 1 | So |
| Speech | 75.069 | 75.400 | Speaker 1 | quick |
| Speech | 75.771 | 79.334 | Speaker 1 | quick [filler] statement, just of the top, our standard price |
| Speech | 80.498 | 81.102 | Speaker 1 | for |
| Speech | 81.513 | 84.093 | Speaker 1 | searching for and doing the paper work for buying home |
| Speech | 84.525 | 89.956 | Speaker 1 | is a thousand dollars. Plus see, you might have even seen our billboard [filler] driving around Texas, |
| Speech | 90.536 | 91.944 | Speaker 1 | [filler] if you have been in Texas, yeah. |
| Speech | 93.197 | 93.608 | Speaker 1 | [filler] |
| Speech | 94.144 | 94.682 | Speaker 1 | but |
| Speech | 95.441 | 99.674 | Speaker 1 | [filler] for a new home or for a special home |
| Speech | 100.206 | 102.248 | Speaker 1 | that may not be the case. So |
| Speech | 102.688 | 105.569 | Speaker 1 | [filler] I just need to ask, you said you are looking for a new home |
| Speech | 106.334 | 113.206 | Speaker 1 | and you want us to be, you know the house of your dreams, are you interested in looking for a home that is already built? |
| Noise | 108.509 | 108.813 | - | - |
| Speech | 114.236 | 118.251 | Speaker 1 | [filler] a home that is preowned but in wonderful condition |
| Speech | 119.028 | 120.855 | Speaker 1 | or do you want to |
| Speech | 121.533 | 124.016 | Speaker 1 | have a house designed and built for you first? |
| Noise | 122.055 | 122.771 | - | - |
| Noise | 124.778 | 125.837 | - | - |
| Speech | 126.075 | 132.288 | Speaker 2 | <initial>OMG</initial> I didnt even know that having my house owned and designed what as an option. |
| Speech | 132.953 | 133.699 | Speaker 2 | [filler] |
| Noise | 133.834 | 134.304 | - | - |
| Speech | 134.264 | 138.338 | Speaker 2 | You know I am kind of (()) spend here because I, I don't think I really. |
| Noise | 138.342 | 138.967 | - | - |
| Speech | 139.377 | 142.520 | Speaker 2 | I don't know. I think I want any and all of them maybe. |
| Speech | 144.036 | 147.639 | Speaker 2 | Maybe you can give me some prices on each of these options. |
| Speech | 149.741 | 157.467 | Speaker 1 | Okay. [filler] so the, the first one in just searching for a home and doing all the paper work for a home that is preowned. |
| Speech | 158.181 | 166.602 | Speaker 1 | [filler] that is the thousand dollar flat fee. We help you search for that. [filler] we contact the owners or we contact the company that is selling it. |
| Speech | 167.324 | 172.443 | Speaker 1 | [filler] we do all the phone calls, all the paper work for you and we report back to you for offers and things like that. |
| Speech | 173.366 | 179.711 | Speaker 1 | [filler] for the second option, if you want to get a new home, we also communicate with the company. |
| Speech | 180.336 | 180.842 | Speaker 1 | [filler] |
TRANSCRIPTION
| TIME | TRANSCRIPT |
|---|---|
| 0.185 0.920 | - |
| 0.364 1.298 | Hello Futurebee. |
| 3.129 3.407 | - |
| 3.415 4.237 | Hello Futurebee. |
| 5.932 10.426 | Hi my name is <PII>Kurt Holt</PII>. You reached [filler] the number one tax realtor. |
| 11.519 13.499 | [filler] can I (()) this call? |
| 14.903 16.829 | Hi this is <PII>Mercedes Holt</PII>. |
| 18.297 26.225 | Okay <PII>Mercedes Holt</PII>. Its good to meet you. [filler] we are, we are happy to help you today. May I ask how, how we are able to help? |
| 22.033 22.635 | - |
| 28.370 34.429 | Yeah [filler] my husband and I are on the market for a brand new beautiful house. |
| 34.877 38.526 | In Texas, we just moved here from California. |
| 39.060 39.975 | And |
| 40.359 50.990 | we are really looking for a nice green house. So we need some help from one of your realtors. [filler] I am calling to ask about pricing, and what kind of packages you guys have because we |
| 51.523 52.966 | really are looking for |
| 53.387 55.835 | by just a shining star of a realtor to help us. |
| 57.710 71.260 | Okay well to be honest I really think you came to the right place. [filler] I have worked for two other real, real estate companies before and I am stuck with this one for ten years because of our (()). I hope we can give you, get you what you need. |
| 72.063 72.266 | - |
| 72.492 73.194 | [filler] |
| 73.825 74.376 | So |
| 75.069 75.400 | quick |
| 75.771 79.334 | quick [filler] statement, just of the top, our standard price |
| 80.498 81.102 | for |
| 81.513 84.093 | searching for and doing the paper work for buying home |
| 84.525 89.956 | is a thousand dollars. Plus see, you might have even seen our billboard [filler] driving around Texas, |
| 90.536 91.944 | [filler] if you have been in Texas, yeah. |
| 93.197 93.608 | [filler] |
| 94.144 94.682 | but |
| 95.441 99.674 | [filler] for a new home or for a special home |
| 100.206 102.248 | that may not be the case. So |
| 102.688 105.569 | [filler] I just need to ask, you said you are looking for a new home |
| 106.334 113.206 | and you want us to be, you know the house of your dreams, are you interested in looking for a home that is already built? |
| 108.509 108.813 | - |
| 114.236 118.251 | [filler] a home that is preowned but in wonderful condition |
| 119.028 120.855 | or do you want to |
| 121.533 124.016 | have a house designed and built for you first? |
| 122.055 122.771 | - |
| 124.778 125.837 | - |
| 126.075 132.288 | <initial>OMG</initial> I didnt even know that having my house owned and designed what as an option. |
| 132.953 133.699 | [filler] |
| 133.834 134.304 | - |
| 134.264 138.338 | You know I am kind of (()) spend here because I, I don't think I really. |
| 138.342 138.967 | - |
| 139.377 142.520 | I don't know. I think I want any and all of them maybe. |
| 144.036 147.639 | Maybe you can give me some prices on each of these options. |
| 149.741 157.467 | Okay. [filler] so the, the first one in just searching for a home and doing all the paper work for a home that is preowned. |
| 158.181 166.602 | [filler] that is the thousand dollar flat fee. We help you search for that. [filler] we contact the owners or we contact the company that is selling it. |
| 167.324 172.443 | [filler] we do all the phone calls, all the paper work for you and we report back to you for offers and things like that. |
| 173.366 179.711 | [filler] for the second option, if you want to get a new home, we also communicate with the company. |
| 180.336 180.842 | [filler] |
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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