Philippine English Call Center Speech Dataset for Travel

This Philippine English speech dataset features real-world call center conversations from the Travel domain. With detailed metadata and accurate transcriptions, it’s designed to power ASR systems, voice AI, and conversational agents.

About this Off-the-shelf Speech Dataset

Introduction

This Philippines English Call Center Speech Dataset for the Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 30 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for English -speaking travelers.

Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.

Speech Data

The dataset includes 30 hours of dual-channel audio recordings between native Philippines English speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.

•Participant Diversity:

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Speakers: 60 native Philippines English contributors from our verified pool.

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Regions: Covering multiple Philippines provinces to capture accent and dialectal variation.

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Participant Profile: Balanced representation of age (18–70) and gender (60% male, 40% female).

•Recording Details:

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Conversation Nature: Naturally flowing, spontaneous customer-agent calls.

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Call Duration: Between 5 and 15 minutes per session.

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Audio Format: Stereo WAV, 16-bit depth, at 8kHz and 16kHz.

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Recording Environment: Captured in controlled, noise-free, echo-free settings.

Topic Diversity

Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).

•Inbound Calls:

•Booking Assistance

•Destination Information

•Flight Delays or Cancellations

•Support for Disabled Passengers

•Health and Safety Travel Inquiries

•Lost or Delayed Luggage, and more

•Outbound Calls:

•Promotional Travel Offers

•Customer Feedback Surveys

•Booking Confirmations

•Flight Rescheduling Alerts

•Visa Expiry Notifications, and others

These scenarios help models understand and respond to diverse traveler needs in real-time.

Transcription

Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.

•Transcription Includes:

•Speaker-Segmented Dialogues

•Time-Stamped Segments

•Non-speech Markers (e.g., pauses, coughs)

•High transcription accuracy by dual-layered transcription review ensures word error rate under 5%.

Metadata

Extensive metadata enriches each call and speaker for better filtering and AI training:

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Participant Metadata: ID, age, gender, region, accent, and dialect.

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Conversation Metadata: Topic, domain, call type, sentiment, and audio specs.

Usage and Applications

This dataset is ideal for a variety of AI use cases in the travel and tourism space:

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ASR Systems: Train English speech-to-text engines for travel platforms.

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Speech Analytics: Uncover customer insights and travel behavior patterns.

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Chatbots & Voice Assistants: Develop English -speaking travel agents.

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Sentiment Detection: Analyze customer tone for better service delivery.

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Generative AI: Fine-tune LLMs for summarizing or responding to traveler requests.

Secure and Ethical Collection

•All data is collected via FutureBeeAI’s secure platform, “Yugo.”

•No personally identifiable information is captured.

•Compliant with data protection regulations and copyright-safe.

Updates and Customization

We regularly expand this dataset with fresh audio and provide custom options:

•Customization Options:

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Environment: Silent, noisy, or varied real-world conditions on request.

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Sample Rate: Adjustable from 8kHz to 48kHz.

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Transcription: Custom formats and QA guidelines available.

License

This travel-focused Philippines English call center dataset is commercially licensed and ready for enterprise or research deployment.

Use Cases

Call Center Conversational AI

Use of speech data for Automatic Speech Recognition

ASR

Chatbot

Language Modelling

TTS

Speech Analytics

Dataset Sample(s)

Dataset Details

Language

English

Language code

en-PH

Country

Philippines

Accents

Tagalog-influenced English, Cebuano-influenced English ...moreIlocano-influenced English, Hiligaynon-influenced English, Kapampangan-influenced English, Chavacano-influenced English

Gender Distribution

M:60, F:40

Age Group

18-70 Years