[et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_fullwidth_image src=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Voice-Data-Collection-and-Transcription-for-AI-Engines.jpg” alt=”Voice Data Collection for AI Engines and Transcription \u2013 Case Study” _builder_version=”4.27.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][\/et_pb_fullwidth_image][\/et_pb_section][et_pb_section fb_built=”1″ fullwidth=”on” _builder_version=”4.18.0″ _module_preset=”default” custom_margin=”2px||0px||false|false” global_colors_info=”{}”][et_pb_fullwidth_post_title meta=”off” featured_image=”off” _builder_version=”4.23.1″ _module_preset=”default” title_text_align=”left” custom_margin=”0px||||false|false” custom_padding=”30px||||false|false” global_colors_info=”{}”][\/et_pb_fullwidth_post_title][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”25px||25px||true|false” global_colors_info=”{}”][et_pb_row module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”20px||20px||true|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.5″ _module_preset=”default” ol_line_height=”1.8em” custom_padding=”||20px||false|false” global_colors_info=”{}” custom_margin=”||13px|||”]<\/p>\n
The case study is about data collection for AI and transcription. The client is a global leader in AI. With a commitment to innovation and customer satisfaction, the client aims to enhance user experience through advanced voice recognition technologies that cater to diverse linguistic demographics.<\/p>\n
The client aimed to train their AI-powered voice assistant for voice command recognition in various local languages. The objective was to create a robust dataset that would enable the AI-powered voice assistant to understand and process voice commands accurately across different demographics, including variations in age, gender, education and regional dialects. The project required the collection of 1,000 hours of audio data for each language, with recordings from individuals representing a wide range of backgrounds. Each participant was expected to provide between 30 minutes to 1 hour of conversational audio.<\/p>\n
The client highlighted the need for high-quality, conversational-type audio recorded in two separate channels, as per stringent technical specifications, to facilitate better training of the AI models.<\/p>\n
To ensure smooth execution and access to regional language speakers, the client required operational support and dedicated recording setups in Hyderabad and Coimbatore to manage participant coordination and recording workflows efficiently.[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”0px||0px||true|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” ol_line_height=”1.8em” custom_padding=”||20px||false|false” global_colors_info=”{}”]<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_3,1_3,1_3″ make_equal=”on” module_class=”inner-page” _builder_version=”4.27.0″ _module_preset=”default” custom_padding=”0px||0px||true|false” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”15px|20px|15px|20px|true|true” border_radii=”on|15px|15px|15px|15px” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” ol_line_height=”1.8em” global_colors_info=”{}”]<\/p>\n
Service:<\/strong> [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.18.0″ _module_preset=”default” custom_padding=”15px|20px|15px|20px|true|true” border_radii=”on|15px|15px|15px|15px” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” ol_line_height=”1.8em” global_colors_info=”{}”]<\/p>\n Languages Covered:<\/strong> [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.18.0″ _module_preset=”default” custom_padding=”15px|20px|15px|20px|true|true” border_radii=”on|15px|15px|15px|15px” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” ol_line_height=”1.8em” global_colors_info=”{}”]<\/p>\n Duration:<\/strong> [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row module_class=”inner-page” _builder_version=”4.27.0″ _module_preset=”default” custom_margin=”20px||||false|false” custom_padding=”||10px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” ol_line_height=”1.8em” global_colors_info=”{}”]<\/p>\n The project presented several challenges that needed to be addressed to meet the client’s requirements effectively:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ make_equal=”on” module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”10px||||false|false” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.23.1″ _module_preset=”default” border_width_all=”1px” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2024\/11\/Version-control-management.png” alt=”Multi-Location Operational Coordination” image_icon_width=”70px” icon_alignment=”left” _builder_version=”4.27.5″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”]<\/p>\n Synchronizing recording activities, participant onboarding, and quality workflows across project hubs in Hyderabad and Coimbatore without compromising standardization.<\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” border_width_all=”1px” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2024\/08\/Cultural-Appropriateness.png” alt=”Diverse Demographics” image_icon_width=”70px” icon_alignment=”left” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”]<\/p>\n Collecting audio samples from a wide range of demographics posed logistical challenges, including identifying suitable participants across various regions and ensuring representation in terms of age, gender and education.<\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ make_equal=”on” module_class=”inner-page” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”||||true|false” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.23.1″ _module_preset=”default” border_width_all=”1px” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2024\/08\/High-Volume-Keywords.png” alt=”Volume of Data” image_icon_width=”70px” icon_alignment=”left” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”]<\/p>\n The requirement for 500-1,000 hours of audio data for each language required extensive planning and coordination to manage the recording sessions efficiently.<\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” border_width_all=”1px” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2024\/11\/secure-document-verification.png” alt=”Quality Control” image_icon_width=”70px” icon_alignment=”left” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”]<\/p>\n Ensuring the quality of the audio recordings was critical. The recordings needed to be clear and representative of natural conversational speech.<\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ make_equal=”on” disabled_on=”off|off|off” module_class=”inner-page” _builder_version=”4.27.5″ _module_preset=”default” custom_padding=”||||true|false” locked=”off” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” border_width_all=”1px” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2024\/11\/Version-control-management.png” alt=”Technical Specifications” image_icon_width=”70px” icon_alignment=”left” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” border_color_all=”rgba(0,0,0,0.51)” global_colors_info=”{}”]<\/p>\n The client specified that audio should be recorded in two separate channels in a conversational format for each participant, which required careful setup and monitoring during the recording process.<\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ disabled_on=”on|on|on” _builder_version=”4.27.5″ _module_preset=”default” border_width_all=”1px” border_color_all=”rgba(0,0,0,0.51)” disabled=”on” global_colors_info=”{}”][\/et_pb_column][\/et_pb_row][et_pb_row module_class=”inner-page” _builder_version=”4.27.0″ _module_preset=”default” custom_padding=”20px||10px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n Fidel implemented an end-to-end strategy to address the client’s requirements and challenges:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ make_equal=”on” module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”10px||||false|false” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.23.1″ _module_preset=”default” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Establishment-of-Recording-Centers.png” alt=”Establishment of Recording Centers” image_icon_width=”60%” _builder_version=”4.27.5″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Fidel established multiple recording centers across various regions, including dedicated operational setups in Hyderabad and Coimbatore, to enable the collection of audio samples. These centers were strategically located to ensure access to diverse demographic groups and to streamline participant coordination and recording workflows.[\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Participant-Recruitment.png” alt=”Participant Recruitment” image_icon_width=”60%” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” global_colors_info=”{}”]<\/p>\n A wide-ranging audience was targeted for participant recruitment. Fidel operated various outreach methods to ensure a representative sample of the population.<\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ make_equal=”on” module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”10px||||false|false” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.23.1″ _module_preset=”default” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Audio-Recording-Process-1.png” alt=”Audio Recording Process” image_icon_width=”60%” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” global_colors_info=”{}”]<\/p>\n The audio data was recorded in two channels to capture natural conversational exchanges. Each session was designed to be interactive, allowing participants to engage in dialogue rather than delivering monologues. This approach ensured that the recordings reflected real-life conversational dynamics.<\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Automated-Transcription-QC-Tool.png” alt=”Automated Transcription QC Tool” image_icon_width=”60%” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” global_colors_info=”{}”]<\/p>\n Developed a custom transcription tools to automate quality checks on active transcribed and batch of files. Integrated an automated quality control mechanism to detect and correct discrepancies in transcriptions. Calculates no-speech duration. Identifies missing punctuations from speech contents. Identifies incorrect abbreviated contents. Enabled efficient timestamp alignment to enhance accuracy and usability of the transcribed data.<\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_2,1_2″ make_equal=”on” module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”10px||||false|false” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.23.1″ _module_preset=”default” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Quality-Assurance.png” alt=”Quality Assurance” image_icon_width=”60%” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” global_colors_info=”{}”]<\/p>\n After the recordings were completed, a rigorous quality control process was implemented. Each audio file was reviewed for clarity and adherence to the client’s specifications. Only recordings that met the high standards set by the client were forwarded for transcription.<\/p>\n [\/et_pb_blurb][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.18.0″ _module_preset=”default” box_shadow_style=”preset1″ global_colors_info=”{}”][et_pb_blurb image=”https:\/\/www.fidelsoftech.com\/case-studies\/wp-content\/uploads\/2025\/03\/Transcription-and-Delivery.png” alt=”Transcription and Delivery” image_icon_width=”60%” _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|20px|20px|20px|true|true” global_colors_info=”{}”]<\/p>\n Following client approval of the recorded audio, we provided transcription services with timestamps. The final deliverables included both the audio files and their corresponding transcriptions, ensuring that the client received a comprehensive dataset for AI training.<\/p>\n [\/et_pb_blurb][\/et_pb_column][\/et_pb_row][et_pb_row module_class=”inner-page” _builder_version=”4.23.1″ _module_preset=”default” custom_padding=”33px||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.18.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n The project was successfully completed within the stipulated timeframe of 8 months to 1 year, delivering high-quality audio data that met the client’s specifications. The key benefits of the project included:<\/p>\n The client received a huge dataset that accurately represented various demographics, enhancing the AI’s ability to understand and process voice commands in multiple languages.<\/p>\n The two-channel recordings captured natural conversational speech, providing the AI with realistic training data that improved its performance in real-world applications.<\/p>\n The structured approach to participant recruitment, recording and quality control ensured that the project was completed on time.<\/p>\n With the newly trained AI<\/a> engines, the client was able to improve user experience across their platforms, leading to increased customer satisfaction and engagement.<\/p>\n Fidel specializes in high-quality data collection and transcription services to support AI-driven applications. If you\u2019re looking for multilingual datasets to enhance your AI models, reach out to us today at sales@fidelsoftech.com<\/a>.<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Section” module_class=”footer-cnt” _builder_version=”4.19.5″ _module_preset=”default” background_color=”#103e66″ custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” locked=”off” global_colors_info=”{}”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.17.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.17.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.23.1″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n If you found this case study similar to your requirement OR interested to get our services, please connect with us using form. We will be happy to respond.<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”]<\/span><\/p>\n
Data Collection<\/a> & Transcription<\/a> for AI-powered voice assistant<\/p>\n
Marathi<\/a>, Hindi<\/a>, Gujarati, Bengali, Tamil, Telugu, Kannada, Malayalam, Punjabi, Odia, Urdu, Simplified Chinese<\/a>, Taiwanese Chinese, Korean<\/a>, Singaporean English, Thai<\/a>, Indonesian<\/a>, Japanese<\/a>, English<\/a><\/p>\n
8 months to 1 year<\/p>\nChallenges Faced:<\/h2>\n
Multi-Location Operational Coordination<\/h3>\n
Diverse Demographics<\/h3>\n
Volume of Data<\/h3>\n
Quality Control<\/h3>\n
Technical Specifications<\/h3>\n
Solutions Provided for Audio Data Collection Services<\/h2>\n
Establishment of Recording Centers<\/h3>\n
Participant Recruitment<\/h3>\n
Audio Recording Process<\/h3>\n
Automated Transcription QC Tools<\/h3>\n
Quality Assurance<\/h3>\n
Transcription and Delivery<\/h3>\n
Results<\/h2>\n
1. Diverse Dataset:<\/h4>\n
2. High-Quality Audio:<\/h4>\n
3. Efficient Process:<\/h4>\n
4. Enhanced AI Capabilities:<\/h4>\n
Connect with Fidel for Voice Data Collection and AI Audio Transcription Services<\/h3>\n
Is this Case Study interests you?<\/h2>\n
<\/i>Call us<\/h3>\n