English (US) Call Center Speech Dataset for Delivery & Logistics

The audio dataset comprises call center conversations for the Delivery & Logistics 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 Delivery and Logistics domain designed to enhance the development of call center speech recognition models specifically for the Delivery and Logistics 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 xscenarios related to the Delivery and Logistics 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:
  • Order Tracking
  • Delivery Complaint
  • Undeliverable Address
  • Delivery Method Selection
  • Return Process Enquiry
  • Order Modification, and many more
  • Outbound Calls:
  • Delivery Confirmation
  • Delivery Subscription
  • Incorrect Address
  • Missed Delivery Attempt
  • Delivery Feedback
  • Out-of-Stock Notification
  • Delivery Satisfaction Survey, 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 Delivery and Logistics 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 Delivery and Logistics 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 Delivery and Logistics sector.
  • Smart Assistants and Chatbots: Developing conversational agents and virtual assistants for customer service in the Delivery and Logistics 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 Delivery and Logistics 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 Delivery and Logistics 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
    Speech0.8921.839Speaker 1Hello Futurebee.
    Speech3.1004.121Speaker 2Hello Futurebee.
    Speech7.23210.375Speaker 1Hi. This is Futurebee Logistics and Delivery. How can I help you?
    Speech11.77517.411Speaker 2Hey. [filler], I am calling, I am getting married in, in two weeks.
    Speech18.06219.068Speaker 2and
    Speech18.98919.507Speaker 1Congrats.
    Speech19.93921.753Speaker 2Yeah. Thank you. Thanks.[filler]
    Speech22.29126.756Speaker 2We are having a destination wedding and it has been kind of a disaster.
    Speech28.02131.001Speaker 2So we had to[filler] switch
    Speech31.62636.530Speaker 2Logistics and Delivery company last minute. So I need you to get me some prices
    Speech37.57940.637Speaker 2and [filler], an estimated delivery time
    Speech41.37843.811Speaker 2[filler] for various items that I need. Can you do that?
    Speech45.42048.134Speaker 1Yeah. Absolutely, absolutely. Where is the destination wedding?
    Speech48.91751.408Speaker 2[filler] it is in Miami, Florida.
    Speech52.66760.344Speaker 1Miami, okay. Alrighty.[filler] We actually do have a branch near Miami. [filler] What are you trying to get delivered?
    Speech62.14971.308Speaker 2Okay, so I have a guy in North Carolina that is going to be sending fresh, [filler], fresh flowers.
    Speech71.91576.730Speaker 2The, they are not for my bouquet. They are just for decorating [filler], the aisle.
    Speech77.26080.709Speaker 2So he is going to be sending about ten pounds
    Speech81.34983.819Speaker 2of fresh flowers. So those need to be kept closed.
    Speech84.83488.185Speaker 2and delivered as fast as possible so they do not wilt.
    Speech88.94190.623Speaker 2That is number one. You got that?
    Speech92.57594.623Speaker 1Yeah. Yeah give me one second.
    Speech95.56697.447Speaker 1[filler] North Carolina,
    Speech98.15399.188Speaker 1fresh flowers
    Speech100.468101.549Speaker 1ten pound
    Speech103.215104.209Speaker 1[filler]
    Speech108.433112.375Speaker 1Okay I have got that [filler] do you also have his contact information?
    Speech113.325119.108Speaker 2[filler] yeah If you give me your email, give me the email of your company, I can
    Speech120.319126.531Speaker 2But I, I want to talk to you first. But if I decide to go through it, then I will go ahead and email you all the details that you want.
    Speech128.598132.251Speaker 1Okay. Alright. That is great. [filler] our email is futurebee
    Speech134.026134.917Speaker 1dot delivery
    Speech135.716136.711Speaker 1at gmail dot com.
    Speech137.449138.341Speaker 2Okay I got it.
    Speech140.747143.741Speaker 1Okay. [filler] you get the flowers from North Carolina whatever
    Speech141.520141.895Speaker 2Okay.
    Speech144.108149.722Speaker 2Yes okay. And then we are having [filler] a special [filler] cake
    Speech150.592153.568Speaker 2made by I do not know, if you have heard of him
    Speech153.860153.989Speaker 2[noise]
    Speech154.364156.479Speaker 2his name is Guy Ferreri
    Speech157.473158.818Speaker 2He is making us
    Speech159.229160.360Speaker 2[filler], custom cake
    Speech161.097165.097Speaker 2And right now he is in New York. So we are going to need to have that cake
    Speech165.925169.205Speaker 2shipped from New York to Miami, Florida.
    Speech169.923173.401Speaker 2And again it needs to stay cold, stay intact
    Speech174.645177.866Speaker 2and needs to stay as fresh as possible because I do not want to feed my guests
    Speech178.745183.574Speaker 2a stale cake. So have you guys delivered food items before like that?

    TRANSCRIPTION

    TIMETRANSCRIPT
    0.892
    1.839
    Hello Futurebee.
    3.100
    4.121
    Hello Futurebee.
    7.232
    10.375
    Hi. This is Futurebee Logistics and Delivery. How can I help you?
    11.775
    17.411
    Hey. [filler], I am calling, I am getting married in, in two weeks.
    18.062
    19.068
    and
    18.989
    19.507
    Congrats.
    19.939
    21.753
    Yeah. Thank you. Thanks.[filler]
    22.291
    26.756
    We are having a destination wedding and it has been kind of a disaster.
    28.021
    31.001
    So we had to[filler] switch
    31.626
    36.530
    Logistics and Delivery company last minute. So I need you to get me some prices
    37.579
    40.637
    and [filler], an estimated delivery time
    41.378
    43.811
    [filler] for various items that I need. Can you do that?
    45.420
    48.134
    Yeah. Absolutely, absolutely. Where is the destination wedding?
    48.917
    51.408
    [filler] it is in Miami, Florida.
    52.667
    60.344
    Miami, okay. Alrighty.[filler] We actually do have a branch near Miami. [filler] What are you trying to get delivered?
    62.149
    71.308
    Okay, so I have a guy in North Carolina that is going to be sending fresh, [filler], fresh flowers.
    71.915
    76.730
    The, they are not for my bouquet. They are just for decorating [filler], the aisle.
    77.260
    80.709
    So he is going to be sending about ten pounds
    81.349
    83.819
    of fresh flowers. So those need to be kept closed.
    84.834
    88.185
    and delivered as fast as possible so they do not wilt.
    88.941
    90.623
    That is number one. You got that?
    92.575
    94.623
    Yeah. Yeah give me one second.
    95.566
    97.447
    [filler] North Carolina,
    98.153
    99.188
    fresh flowers
    100.468
    101.549
    ten pound
    103.215
    104.209
    [filler]
    108.433
    112.375
    Okay I have got that [filler] do you also have his contact information?
    113.325
    119.108
    [filler] yeah If you give me your email, give me the email of your company, I can
    120.319
    126.531
    But I, I want to talk to you first. But if I decide to go through it, then I will go ahead and email you all the details that you want.
    128.598
    132.251
    Okay. Alright. That is great. [filler] our email is futurebee
    134.026
    134.917
    dot delivery
    135.716
    136.711
    at gmail dot com.
    137.449
    138.341
    Okay I got it.
    140.747
    143.741
    Okay. [filler] you get the flowers from North Carolina whatever
    141.520
    141.895
    Okay.
    144.108
    149.722
    Yes okay. And then we are having [filler] a special [filler] cake
    150.592
    153.568
    made by I do not know, if you have heard of him
    153.860
    153.989
    [noise]
    154.364
    156.479
    his name is Guy Ferreri
    157.473
    158.818
    He is making us
    159.229
    160.360
    [filler], custom cake
    161.097
    165.097
    And right now he is in New York. So we are going to need to have that cake
    165.925
    169.205
    shipped from New York to Miami, Florida.
    169.923
    173.401
    And again it needs to stay cold, stay intact
    174.645
    177.866
    and needs to stay as fresh as possible because I do not want to feed my guests
    178.745
    183.574
    a stale cake. So have you guys delivered food items before like that?

    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

    Dual separate channel

    Audio file duration

    5-15 minutes

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