English (US) Call Center Speech Dataset for Healthcare

The audio dataset comprises call center conversations for the Healthcare 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

About Gradiet Line

Introduction

Welcome to the US English Call Center Speech Dataset for the Healthcare domain designed to enhance the development of call center speech recognition models specifically for the Healthcare 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 Healthcare domain, designed to build robust and accurate customer service speech technology.

  • Participant Diversity:
  • 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.
  • Recording Details:
  • 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.

  • Inbound Calls:
  • Appointment Scheduling
  • New Patient Registration
  • Surgery Consultation
  • Consultation regarding Diet, and many more
  • Outbound Calls:
  • Appointment Reminder
  • Health and Wellness Subscription Programs
  • Lab Tests Results
  • Health Risk Assessments
  • Preventive Care Reminders, 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 Healthcare 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 Healthcare 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 Healthcare sector.
  • Smart Assistants and Chatbots: Developing conversational agents and virtual assistants for customer service in the Healthcare 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 Healthcare 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.

  • Customization & Custom Collection Options:
  • 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 Healthcare domain call center audio dataset is created by FutureBeeAI and is available for commercial use.

    Use Cases

    Use of speech data in Conversational AI

    Call Center Conversational AI

    Use of speech data for Automatic Speech Recognition

    ASR

    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)

    Sample Line

    ATTRIBUTES

    Channel 1Channel 2Format
    Male(29)Female(24)wav, json

    TRANSCRIPTION

    LABELSTARTENDCHANNELTRANSCRIPT
    Speech4.7745.799Speaker 2Hello Futurebee.
    Speech7.5788.477Speaker 1Hello Futurebee.
    Noise7.7037.961--
    Noise9.5199.878--
    Speech12.66914.336Speaker 2Hello is this <PII>Mr. Micheal</PII>?
    Speech15.57917.335Speaker 1This is, whom I speaking to?
    Speech18.56224.603Speaker 2Hi this is Kelly. I am with [filler], Dr Brigers office. [filler] I am calling because we
    Noise24.32924.518--
    Speech25.08226.722Speaker 2needed you a little pre test
    Speech27.36129.411Speaker 2screening before your appointment tomorrow.
    Speech30.10331.312Speaker 2You have just ten minutes.
    Speech33.86837.679Speaker 1[filler] yeah I think so. [filler] yeah, yeah I have got.
    Noise37.72238.222--
    Speech39.20744.883Speaker 2Okay perfect. So we just do this phone call to make the check in process easier once you get here because
    Speech45.64947.847Speaker 2ever since our office is reopened
    Speech48.28350.347Speaker 2we had such a backlog of patients
    Speech51.02453.265Speaker 2that when we reopened
    Noise52.81654.182--
    Speech54.13360.191Speaker 2we are trying to take on more patients than usual. So by doing this process it helps us to get through
    Speech60.74061.731Speaker 2the check in process
    Speech61.95765.248Speaker 2more quickly when you actually come to the office. Okay?
    Speech68.32875.453Speaker 1I will tell you what, that makes me real happy because one of the things I hate about going into doctors offices is I get there in time to my appointment.
    Speech75.89481.087Speaker 1And then I get a quick half an hour to call out all the paper work. That's in a, that's in a eliminate this right?
    Speech83.28786.912Speaker 2For the most part, [filler] thankfully you are already [filler]
    Speech87.55290.194Speaker 2repeat patient that we won't have to call out
    Speech90.58791.686Speaker 2any paper work
    Speech92.43695.052Speaker 2like sometimes you have to do with your new patient.
    Speech95.953100.677Speaker 2[filler], but I just want you to know that like I said we have been really
    Speech101.403103.453Speaker 2swamped with new patients and
    Speech103.843105.686Speaker 2a backlog of patients so
    Speech106.170108.412Speaker 2please continue to be patient with us if you are
    Speech108.811110.569Speaker 2Appointment is on perfectly on time.
    Speech114.045116.670Speaker 1Okay. Alright [filler], thanks for giving me a heads up.
    Speech117.203120.170Speaker 2Alright so I just have a few questions to ask you.
    Speech121.927126.644Speaker 2[filler] and they are just some general questions about your health within the last few days.
    Speech127.412131.703Speaker 2So just think back to your last few days and you can give me an answer. Are you ready?
    Speech135.287135.961Speaker 1I am ready.
    Speech135.453138.978Speaker 2Okay my first question is, have you had a new fever?
    Speech139.425145.336Speaker 2of a hundred and four degrees or higher, Of one hundred point four degrees or higher? Yes or no?
    Speech148.151156.961Speaker 1[filler], I have not had any meter to take my own temperature in the last forty eight hours. I have a sense of fever. So [filler], I don't have any measurements to tell you this. But no, I, I don't.
    Noise157.032157.663--
    Speech158.788163.216Speaker 2Okay so that means that within the last couple of days there has been no symptoms that could be
    Noise159.274160.066--
    Speech163.757165.532Speaker 2connected with a fever either right?
    Speech167.757168.191Speaker 1Correct
    Speech169.223172.032Speaker 2Okay that's great. Let me just type that into my computer.
    Noise172.626172.723--
    Speech174.830176.247Speaker 2Okay and my next question.
    Speech176.782181.449Speaker 2Have you had a new cough, you can now attribute to another health condition?

    TRANSCRIPTION

    TIMETRANSCRIPT
    4.774
    5.799
    Hello Futurebee.
    7.578
    8.477
    Hello Futurebee.
    7.703
    7.961
    -
    9.519
    9.878
    -
    12.669
    14.336
    Hello is this <PII>Mr. Micheal</PII>?
    15.579
    17.335
    This is, whom I speaking to?
    18.562
    24.603
    Hi this is Kelly. I am with [filler], Dr Brigers office. [filler] I am calling because we
    24.329
    24.518
    -
    25.082
    26.722
    needed you a little pre test
    27.361
    29.411
    screening before your appointment tomorrow.
    30.103
    31.312
    You have just ten minutes.
    33.868
    37.679
    [filler] yeah I think so. [filler] yeah, yeah I have got.
    37.722
    38.222
    -
    39.207
    44.883
    Okay perfect. So we just do this phone call to make the check in process easier once you get here because
    45.649
    47.847
    ever since our office is reopened
    48.283
    50.347
    we had such a backlog of patients
    51.024
    53.265
    that when we reopened
    52.816
    54.182
    -
    54.133
    60.191
    we are trying to take on more patients than usual. So by doing this process it helps us to get through
    60.740
    61.731
    the check in process
    61.957
    65.248
    more quickly when you actually come to the office. Okay?
    68.328
    75.453
    I will tell you what, that makes me real happy because one of the things I hate about going into doctors offices is I get there in time to my appointment.
    75.894
    81.087
    And then I get a quick half an hour to call out all the paper work. That's in a, that's in a eliminate this right?
    83.287
    86.912
    For the most part, [filler] thankfully you are already [filler]
    87.552
    90.194
    repeat patient that we won't have to call out
    90.587
    91.686
    any paper work
    92.436
    95.052
    like sometimes you have to do with your new patient.
    95.953
    100.677
    [filler], but I just want you to know that like I said we have been really
    101.403
    103.453
    swamped with new patients and
    103.843
    105.686
    a backlog of patients so
    106.170
    108.412
    please continue to be patient with us if you are
    108.811
    110.569
    Appointment is on perfectly on time.
    114.045
    116.670
    Okay. Alright [filler], thanks for giving me a heads up.
    117.203
    120.170
    Alright so I just have a few questions to ask you.
    121.927
    126.644
    [filler] and they are just some general questions about your health within the last few days.
    127.412
    131.703
    So just think back to your last few days and you can give me an answer. Are you ready?
    135.287
    135.961
    I am ready.
    135.453
    138.978
    Okay my first question is, have you had a new fever?
    139.425
    145.336
    of a hundred and four degrees or higher, Of one hundred point four degrees or higher? Yes or no?
    148.151
    156.961
    [filler], I have not had any meter to take my own temperature in the last forty eight hours. I have a sense of fever. So [filler], I don't have any measurements to tell you this. But no, I, I don't.
    157.032
    157.663
    -
    158.788
    163.216
    Okay so that means that within the last couple of days there has been no symptoms that could be
    159.274
    160.066
    -
    163.757
    165.532
    connected with a fever either right?
    167.757
    168.191
    Correct
    169.223
    172.032
    Okay that's great. Let me just type that into my computer.
    172.626
    172.723
    -
    174.830
    176.247
    Okay and my next question.
    176.782
    181.449
    Have you had a new cough, you can now attribute to another health condition?

    Dataset Demographics

    Details Headline

    Language

    English

    Language code

    en-us

    Country

    USA

    Accents

    Arizona,...more

    Gender Distribution

    M:60, F:40

    Age Group

    18-70

    Audio File Details

    Details Headline

    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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