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Gujarati (India) Call Center Speech Dataset for Travel

The audio dataset comprises call center conversations for the Travel domain, featuring native Gujarati speakers from India. 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 Gujarati 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.

  • •Participant Diversity:
  • •
    Speakers: 60 expert native Gujarati speakers from the FutureBeeAI Community.
  • •
    Regions: Different regions of Gujarat, ensuring a balanced representation of Gujarati 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:
  • •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
  • •Outbound Calls:
  • •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 Gujarati 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 Gujarati 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 Gujarati.
  • •
    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.

  • •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 Travel 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(34)Female(30)wav, json

    TRANSCRIPTION

    LABELSTARTENDCHANNELTRANSCRIPT
    Speech0.5002.200Speaker 2<lang:Foreign>Hello futurebee Hello futurebee</lang:Foreign>.
    Speech2.9235.000Speaker 1<lang:Foreign>Hello futurebee</lang:Foreign>.
    Speech6.82510.925Speaker 2<lang:Foreign>Hello</lang:Foreign>, તમે <lang:Foreign>gateway tours and travels</lang:Foreign> માંથી વાત કરી રહ્યા છો?
    Speech11.47418.250Speaker 1હા હું <lang:Foreign>gateway tours and travels</lang:Foreign> માંથી વાત કરી રહ્યો છું. બોલો તમારી શું <lang:Foreign>help</lang:Foreign> કરી શકું હું?
    Noise18.82419.524--
    Noise20.14920.653--
    Speech20.65527.475Speaker 2મારે <lang:Foreign>tour</lang:Foreign> માટે જવાનું હતું તો તમે મને જણાવી શકો કે તમારી પાસે કયા કયા <lang:Foreign>packages</lang:Foreign> ઉપલબ્ધ છે?
    Speech28.42540.075Speaker 1હા મારી પાસે ગણા બધા <lang:Foreign>packages</lang:Foreign> ઉપલબ્ધ છે. પણ તમે મને કઈ શકો તમારે ક્યાં જવું છે? <lang:Foreign>India</lang:Foreign> માં <lang:Foreign>travel</lang:Foreign> કરવું છે કે <lang:Foreign>foreign</lang:Foreign> માં જવું છે?
    Speech41.71944.520Speaker 2તમારી પાસે <lang:Foreign>foreign trip</lang:Foreign> પણ <lang:Foreign>available</lang:Foreign> છે?
    Speech44.42050.195Speaker 1હા મારા પાસે <lang:Foreign>foreign trip available</lang:Foreign> છે. તમારે <lang:Foreign>foreign</lang:Foreign> ફરવા જવું છે?
    Speech52.24359.542Speaker 2#આહ અત્યાર માટે તો <lang:Foreign>India</lang:Foreign> માં જ જવું છે. તમે જણાવી શકો કે <lang:Foreign>India</lang:Foreign> માં તમારી પાસે કયા કયા <lang:Foreign>packages</lang:Foreign> ઉપલબ્ધ છે?
    Speech59.74368.444Speaker 1અમારી પાસે <lang:Foreign>all over India</lang:Foreign> ના <lang:Foreign>packages available</lang:Foreign> છે. <lang:Foreign>Jammu Kashmir</lang:Foreign> ના પણ છે, રાજસ્થાન પણ છે
    Speech69.26977.668Speaker 1પછી ચેન્નઇ પણ છે ઓરિસા પણ છે. તમારે ક્યાં જવું છે? તમે <lang:Foreign>fix</lang:Foreign> કોઈ <lang:Foreign>destination</lang:Foreign> નક્કી કર્યું છે?
    Speech69.99270.894Speaker 2હા
    Speech79.91889.918Speaker 2હા અમારે ઉત્તર પ્રદેશ બાજુ જવું છે <lang:Foreign>Kashmir</lang:Foreign> થી લઇ ને સિમલા મનાલી સુધી બધા <lang:Foreign>station cover</lang:Foreign> થઇ જાય એવું છે તમારી જોડે?
    Speech90.39494.418Speaker 1હા અમારી પાસે છે <lang:Foreign>multiple destination</lang:Foreign> ના બધા
    Speech94.81996.093Speaker 2<lang:Foreign>Okay, okay</lang:Foreign>.
    Speech95.718100.519Speaker 1<lang:Foreign>Packages available</lang:Foreign> તો તમારે કેટલા દિવસો માટે જવું છે?
    Speech97.91898.593Speaker 2હા
    Speech102.918105.543Speaker 2તમારા <lang:Foreign>packages</lang:Foreign> માં કેટલા દિવસો નું છે?
    Speech105.418109.093Speaker 1અમારું <lang:Foreign>package multiple destination</lang:Foreign> નું છે તે
    Speech110.144114.543Speaker 1છ દિવસ નું છે, <lang:Foreign>week</lang:Foreign> નું છે, <lang:Foreign>ten days</lang:Foreign> છે.
    Speech114.894118.694Speaker 1<lang:Foreign>Fifteen days</lang:Foreign> છે અને <lang:Foreign>one month</lang:Foreign> નું પણ <lang:Foreign>available</lang:Foreign> છે.
    Speech121.343127.319Speaker 2<lang:Foreign>Okay but one week</lang:Foreign> માટે તમારા પાસે કયા કયા છે અમને <lang:Foreign>one week</lang:Foreign> માટે જણાઈ શકો તમે?
    Speech127.194132.687Speaker 1હા અમારી પાસે <lang:Foreign>one week</lang:Foreign> ના પણ છે <lang:Foreign>available</lang:Foreign>. અમારી પાસે <lang:Foreign>one week</lang:Foreign> ના
    Speech132.739133.389Speaker 2હા
    Speech133.587140.062Speaker 1ત્રણ, ત્રણ <lang:Foreign>packages available</lang:Foreign> છે અત્યારે સિમલા મનાલી એ <lang:Foreign>side</lang:Foreign> ના.
    Speech141.663145.014Speaker 1જેમાં એક માં
    Speech143.014144.014Speaker 2<lang:Foreign>Okay</lang:Foreign>.
    Speech145.639150.139Speaker 1<lang:Foreign>three days</lang:Foreign> અને <lang:Foreign>four nights</lang:Foreign> છે અને એક માં
    Speech151.437153.337Speaker 1<lang:Foreign>I means</lang:Foreign> બીજા બે માં
    Speech153.739154.538Speaker 2હા
    Speech154.337158.986Speaker 1<lang:Foreign>four days and three nights</lang:Foreign> છે તમારે કેમ જવું છે?
    Speech161.336165.586Speaker 2મતલબ <lang:Foreign>one week</lang:Foreign> માં બધા <lang:Foreign>station cover</lang:Foreign> થઇ જશે?
    Speech166.611168.361Speaker 1હા હા થઇ જશે.
    Speech169.812179.086Speaker 2<lang:Foreign>Okay</lang:Foreign>, તો અમને મતલબ <lang:Foreign>one week</lang:Foreign> માટે નું જ જોઈએ છે તો તમે એની <lang:Foreign>process</lang:Foreign> જણાઈ શકો કે કઈ રીતનું <lang:Foreign>transport</lang:Foreign> અમારું રહેશે?
    Noise172.312173.361--
    Speech180.538185.711Speaker 1તમે ક્યાં થી બોલો છો તમારું <lang:Foreign>resident area</lang:Foreign> ક્યાં છે?

    TRANSCRIPTION

    TIMETRANSCRIPT
    0.500
    2.200    		<lang:Foreign>Hello futurebee Hello futurebee</lang:Foreign>.
    2.923
    5.000    		<lang:Foreign>Hello futurebee</lang:Foreign>.
    6.825
    10.925    		<lang:Foreign>Hello</lang:Foreign>, તમે <lang:Foreign>gateway tours and travels</lang:Foreign> માંથી વાત કરી રહ્યા છો?
    11.474
    18.250    		હા હું <lang:Foreign>gateway tours and travels</lang:Foreign> માંથી વાત કરી રહ્યો છું. બોલો તમારી શું <lang:Foreign>help</lang:Foreign> કરી શકું હું?
    18.824
    19.524    		-
    20.149
    20.653    		-
    20.655
    27.475    		મારે <lang:Foreign>tour</lang:Foreign> માટે જવાનું હતું તો તમે મને જણાવી શકો કે તમારી પાસે કયા કયા <lang:Foreign>packages</lang:Foreign> ઉપલબ્ધ છે?
    28.425
    40.075    		હા મારી પાસે ગણા બધા <lang:Foreign>packages</lang:Foreign> ઉપલબ્ધ છે. પણ તમે મને કઈ શકો તમારે ક્યાં જવું છે? <lang:Foreign>India</lang:Foreign> માં <lang:Foreign>travel</lang:Foreign> કરવું છે કે <lang:Foreign>foreign</lang:Foreign> માં જવું છે?
    41.719
    44.520    		તમારી પાસે <lang:Foreign>foreign trip</lang:Foreign> પણ <lang:Foreign>available</lang:Foreign> છે?
    44.420
    50.195    		હા મારા પાસે <lang:Foreign>foreign trip available</lang:Foreign> છે. તમારે <lang:Foreign>foreign</lang:Foreign> ફરવા જવું છે?
    52.243
    59.542    		#આહ અત્યાર માટે તો <lang:Foreign>India</lang:Foreign> માં જ જવું છે. તમે જણાવી શકો કે <lang:Foreign>India</lang:Foreign> માં તમારી પાસે કયા કયા <lang:Foreign>packages</lang:Foreign> ઉપલબ્ધ છે?
    59.743
    68.444    		અમારી પાસે <lang:Foreign>all over India</lang:Foreign> ના <lang:Foreign>packages available</lang:Foreign> છે. <lang:Foreign>Jammu Kashmir</lang:Foreign> ના પણ છે, રાજસ્થાન પણ છે
    69.269
    77.668    		પછી ચેન્નઇ પણ છે ઓરિસા પણ છે. તમારે ક્યાં જવું છે? તમે <lang:Foreign>fix</lang:Foreign> કોઈ <lang:Foreign>destination</lang:Foreign> નક્કી કર્યું છે?
    69.992
    70.894    		હા
    79.918
    89.918    		હા અમારે ઉત્તર પ્રદેશ બાજુ જવું છે <lang:Foreign>Kashmir</lang:Foreign> થી લઇ ને સિમલા મનાલી સુધી બધા <lang:Foreign>station cover</lang:Foreign> થઇ જાય એવું છે તમારી જોડે?
    90.394
    94.418    		હા અમારી પાસે છે <lang:Foreign>multiple destination</lang:Foreign> ના બધા
    94.819
    96.093    		<lang:Foreign>Okay, okay</lang:Foreign>.
    95.718
    100.519    		<lang:Foreign>Packages available</lang:Foreign> તો તમારે કેટલા દિવસો માટે જવું છે?
    97.918
    98.593    		હા
    102.918
    105.543    		તમારા <lang:Foreign>packages</lang:Foreign> માં કેટલા દિવસો નું છે?
    105.418
    109.093    		અમારું <lang:Foreign>package multiple destination</lang:Foreign> નું છે તે
    110.144
    114.543    		છ દિવસ નું છે, <lang:Foreign>week</lang:Foreign> નું છે, <lang:Foreign>ten days</lang:Foreign> છે.
    114.894
    118.694    		<lang:Foreign>Fifteen days</lang:Foreign> છે અને <lang:Foreign>one month</lang:Foreign> નું પણ <lang:Foreign>available</lang:Foreign> છે.
    121.343
    127.319    		<lang:Foreign>Okay but one week</lang:Foreign> માટે તમારા પાસે કયા કયા છે અમને <lang:Foreign>one week</lang:Foreign> માટે જણાઈ શકો તમે?
    127.194
    132.687    		હા અમારી પાસે <lang:Foreign>one week</lang:Foreign> ના પણ છે <lang:Foreign>available</lang:Foreign>. અમારી પાસે <lang:Foreign>one week</lang:Foreign> ના
    132.739
    133.389    		હા
    133.587
    140.062    		ત્રણ, ત્રણ <lang:Foreign>packages available</lang:Foreign> છે અત્યારે સિમલા મનાલી એ <lang:Foreign>side</lang:Foreign> ના.
    141.663
    145.014    		જેમાં એક માં
    143.014
    144.014    		<lang:Foreign>Okay</lang:Foreign>.
    145.639
    150.139    		<lang:Foreign>three days</lang:Foreign> અને <lang:Foreign>four nights</lang:Foreign> છે અને એક માં
    151.437
    153.337    		<lang:Foreign>I means</lang:Foreign> બીજા બે માં
    153.739
    154.538    		હા
    154.337
    158.986    		<lang:Foreign>four days and three nights</lang:Foreign> છે તમારે કેમ જવું છે?
    161.336
    165.586    		મતલબ <lang:Foreign>one week</lang:Foreign> માં બધા <lang:Foreign>station cover</lang:Foreign> થઇ જશે?
    166.611
    168.361    		હા હા થઇ જશે.
    169.812
    179.086    		<lang:Foreign>Okay</lang:Foreign>, તો અમને મતલબ <lang:Foreign>one week</lang:Foreign> માટે નું જ જોઈએ છે તો તમે એની <lang:Foreign>process</lang:Foreign> જણાઈ શકો કે કઈ રીતનું <lang:Foreign>transport</lang:Foreign> અમારું રહેશે?
    172.312
    173.361    		-
    180.538
    185.711    		તમે ક્યાં થી બોલો છો તમારું <lang:Foreign>resident area</lang:Foreign> ક્યાં છે?

    Dataset Demographics

    Details Headline

    Language

    Gujarati

    Language code

    gu-in

    Country

    India

    Accents

    Kathiawari,...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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