1. Overview With extensive experience in speech recognition, Nexdata has resource pool covering more than 50 countries and regions. Our linguist team works closely with clients to assist them with dictionary and text corpus construction, speech quality inspection, linguistics consulting and etc.

2. Our Capacity -Global Resources: Global resources covering hundreds of languages worldwide

-Compliance: All the Machine Learning (ML) Data are collected with proper authorization -Quality: Multiple rounds of quality inspections ensures high quality data output

-Secure Implementation: NDA is signed to gurantee secure implementation and Machine Learning (ML) Data is destroyed upon delivery.

1. About Nexdata Nexdata is equipped with professional Machine Learning (ML) Data collection devices, tools and environments, as well as experienced project managers in data collection and quality control, so that we can meet the data collection requirements in various scenarios and types. Please visit us at https://www.nexdata.ai/service/speech-recognition?source=Datarade

Nexdata is equipped with professional recording equipment and has resources pool of 70+ countries and regions, and provide various types of speech recognition data collection services for Machine Learning (ML) Data.

Nexdata provides multi-language, multi-timbre, multi-domain and multi-style speech synthesis data collection servicesfor Deep Learning Data.

1. Overview
2. Unsupervised Learning: For the training data required in unsupervised learning, Nexdata delivers data collection and cleaning services for both single-modal and cross-modal data. We provide Large Language Model(LLM) Data cleaning and personnel support services based on the specific data types and characteristics of the client's domain.

-SFT: Nexdata assists clients in generating high-quality supervised fine-tuning data for model optimization through prompts and outputs annotation.

-Red teaming: Nexdata helps clients train and validate models through drafting various adversarial attacks, such as exploratory or potentially harmful questions. Our red team capabilities help clients identify problems in their models related to hallucinations, harmful content, false information, discrimination, language bias and etc.

-RLHF: Nexdata assist clients in manually ranking multiple outputs generated by the SFT-trained model according to the rules provided by the client, or provide multi-factor scoring. By training annotators to align with values and utilizing a multi-person fitting approach, the quality of feedback can be improved.

1. Our Capacity -Global Resources: Global resources covering hundreds of languages worldwide

-Compliance: All the Large Language Model(LLM) Data is collected with proper authorization

-Quality: Multiple rounds of quality inspections ensures high quality data output

-Secure Implementation: NDA is signed to gurantee secure implementation and data is destroyed upon delivery.

-Efficency: Our platform supports human-machine interaction and semi-automatic labeling, increasing labeling efficiency by more than 30% per annotator. It has successfully been applied to nearly 5,000 projects.

3.About Nexdata Nexdata is equipped with professional data collection devices, tools and environments, as well as experienced project managers in data collection and quality control, so that we can meet the Large Language Model(LLM) Data collection requirements in various scenarios and types. We have global data processing centers and more than 20,000 professional annotators, supporting on-demand Large Language Model(LLM) Data annotation services, such as speech, image, video, point cloud and Natural Language Processing (NLP) Data, etc. Please visit us at https://www.nexdata.ai/?source=Datarade

Market Size and Growth: The global speech and audio data market size is projected to reach USD XXX million by 2033, expanding at a robust CAGR of XX% between 2025 and 2033. This growth is primarily driven by the increasing adoption of voice-controlled devices and services, rising demand for automated customer support, and advancements in artificial intelligence (AI) and machine learning (ML) technologies. Drivers and Trends: The market growth is further fueled by the growing popularity of smart speakers, home assistants, and voice-based commerce. Moreover, the integration of speech recognition and natural language processing (NLP) capabilities into various applications, such as healthcare, education, and entertainment, is expected to drive demand for speech and audio data. Additionally, the rise of AI-powered voicebots and virtual assistants is automating customer interactions and improving operational efficiency, further contributing to market expansion. The speech and audio data market is highly concentrated, with a few major players controlling a significant share of the market. These players include Google, Baidu, Iflytek, Facebook, Amazon, Apple Inc., IBM, Microsoft, Brianasoft, Neurotechnology, Sensory Inc., VoiceBase, Auraya, LumenVox, and Speechocean. The market is characterized by a high level of innovation, with new technologies and products being introduced regularly. The impact of regulations on the market is also significant, as they can affect the way that companies collect, store, and use speech and audio data. The end user concentration in the market is relatively low, with a wide range of businesses and consumers using speech and audio data technologies. The level of M&A activity in the market is also relatively high, as companies seek to acquire new technologies and capabilities.

The AI Data Resource Service market is experiencing robust growth, driven by the increasing adoption of artificial intelligence across diverse sectors. This market, encompassing services like computer vision data annotation, speech recognition data collection, and natural language processing data creation, is projected to reach a substantial size. While the exact 2025 market size isn't provided, considering typical growth rates in the technology sector and the expanding applications of AI, a reasonable estimate would be $15 billion. Assuming a conservative Compound Annual Growth Rate (CAGR) of 25% over the forecast period (2025-2033), the market is poised to exceed $100 billion by 2033. This impressive growth is fueled by several key drivers, including the expanding demand for AI-powered applications in education, government, and enterprise, as well as the continuous advancements in AI algorithms that necessitate high-quality training data. Significant trends within the market include the rise of synthetic data generation to supplement real-world data and the increasing demand for specialized data annotation services catering to specific AI model requirements. However, restraints include challenges in data privacy and security, the need for skilled data annotation professionals, and the high costs associated with data acquisition and labeling. The segmentation of the AI Data Resource Service market reveals strong growth across all application areas. Educational institutions are increasingly leveraging AI for personalized learning, while governments are employing AI for enhanced public services and national security. Enterprises are adopting AI to improve operational efficiency, enhance customer experience, and gain a competitive edge. Key players like Appen, Amazon, Google, and others are heavily investing in expanding their data annotation capabilities, fostering innovation and competition within this rapidly evolving market. The geographical distribution shows significant market presence across North America and Europe, with Asia Pacific emerging as a rapidly growing region. Future growth will be influenced by government policies supporting AI adoption, advancements in data annotation technologies, and the ongoing expansion of AI applications across various industry verticals. The market's ongoing expansion necessitates a strategic approach encompassing data quality assurance, ethical data sourcing, and the development of robust data governance frameworks.

Italian(Italy) Scripted Monologue Smartphone speech dataset, collected from monologue based on given common-used sentences, with balanced gender distribution. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers(800 people), geographicly speaking, enhancing model performance in real and complex tasks.Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

We provide a wide range of off-the-shelf multilingual audio datasets, featuring real-world call center dialogues and general conversational recordings from regions across Africa, Central America, South America, and Asia.

Our datasets include multiple languages, local dialects, and authentic conversational flows — designed for AI training, contact center automation, and conversational AI development. All samples are human-validated and come with complete metadata.

Each Dataset Includes:

Unique Participant ID

Gender (Male/Female)

Country & City of Origin

Speaker Age (18-60 years)

Language (English + Multiple Local Languages)

Audio Length: ~30 minutes per participant

Validation Status: 100% Human-Checked

Why Work With Us: ✅ Large library of ready-to-use multilingual datasets ✅ Authentic call center, customer service, and natural conversation recordings ✅ Global coverage with diverse speaker demographics ✅ Custom data collection service — we can source or record datasets tailored to your language, region, or domain needs

Best For:

Speech Recognition & Multilingual NLP

Voicebots & Contact Center AI Solutions

Dialect & Accent Recognition Training

Conversational AI & Multilingual Assistants

Customer Support & Quality Analytics

Whether you need off-the-shelf datasets or unique, project-specific collections — we’ve got you covered.

http://filemarket.ai

The global voice data services market is experiencing robust growth, driven by the increasing adoption of voice-enabled technologies across various sectors. The market's expansion is fueled by the surge in demand for accurate and efficient transcription, translation, and analysis of voice data. This demand stems from several key factors, including the proliferation of virtual assistants, smart speakers, and contact center solutions, all reliant on sophisticated voice data processing. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) are leading to more accurate and cost-effective voice data solutions, further stimulating market growth. We estimate the market size in 2025 to be $5 billion, based on observed growth in related sectors like AI and the increasing adoption of voice technologies. A Compound Annual Growth Rate (CAGR) of 15% is projected for the forecast period (2025-2033), indicating a significant expansion of the market in the coming years. Key market segments include transcription services, translation services, and voice analytics. Leading companies like SpeechOcean, Nexdata, and others are actively shaping market dynamics through technological innovation and strategic partnerships. However, challenges remain, including data privacy concerns and the need for robust data security measures to ensure responsible and ethical use of voice data. The market's future trajectory is strongly linked to advancements in AI and natural language processing (NLP). Continued improvements in speech recognition accuracy, coupled with the development of more sophisticated voice biometric systems, will unlock new opportunities within healthcare, finance, and customer service industries. While data security and privacy remain significant concerns, regulatory developments and technological advancements are addressing these issues. The increasing adoption of cloud-based solutions is also driving efficiency and scalability within the voice data services market, reducing costs and increasing accessibility for businesses of all sizes. The competitive landscape is characterized by both established players and emerging startups, with companies focusing on innovation and differentiation through specialized services and targeted solutions. Geographic expansion, particularly in developing economies with growing digital infrastructure, is expected to significantly contribute to overall market growth.

The global speech and audio data market is experiencing robust growth, driven by the increasing adoption of voice assistants, the proliferation of smart devices, and the expanding use of speech analytics in various sectors. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 18% from 2025 to 2033, reaching an estimated $50 billion by 2033. Key drivers include advancements in artificial intelligence (AI), particularly in natural language processing (NLP) and machine learning (ML), which are enhancing the accuracy and efficiency of speech recognition and analysis. Furthermore, the growing demand for personalized user experiences, coupled with the rise of multilingual applications, is fueling market expansion. The market is segmented by language (Chinese Mandarin, English, Spanish, French, and Others) and application (Commercial Use and Academic Use). Commercial applications, including customer service, market research, and healthcare, currently dominate, but the academic sector is showing significant growth potential as research into speech technology advances. Geographic distribution shows North America and Europe currently holding the largest market shares, but the Asia-Pacific region is expected to experience the fastest growth in the coming years, fueled by increasing smartphone penetration and digitalization in emerging economies like India and China. Restraints include data privacy concerns, the need for high-quality data collection, and the challenges associated with handling diverse accents and dialects. The competitive landscape is characterized by a mix of large technology companies like Google, Amazon, and Microsoft, and specialized speech technology providers such as Nuance and VoiceBase. These companies are engaged in intense R&D to improve the accuracy and performance of speech recognition and synthesis technologies. Strategic partnerships and acquisitions are expected to shape the market further, as companies seek to expand their product portfolios and geographic reach. The ongoing innovation in speech-to-text and text-to-speech technologies, alongside the integration of speech data with other data types (like text and image data), will unlock new applications and further accelerate market growth. The demand for real-time transcription and translation services is also contributing to this upward trend, driving investment in innovative solutions and pushing the boundaries of what’s possible with speech and audio data.

English(the United States) Scripted Monologue Smartphone speech dataset, collected from monologue based on given scripts, covering generic domain, human-machine interaction, smart home command and in-car command, numbers and other domains. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers(1,842 American in total), geographicly speaking, enhancing model performance in real and complex tasks.Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

Get high-quality English call center speech dataset for credit card services. Ideal for AI training, speech recognition, and NLP applications.

Nexdata provides high-quality Speech Data services for speech cleaning, speech transcription, phoneme annotation etc, with word accuracy of 99.5% and phoneme segmentation of 0.01s.

Introduction

This Colombian Spanish Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Spanish-speaking customers. Featuring over 30 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Colombian Spanish speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.

This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making financial domain model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

The global voice synthesis data service market is projected to grow from XXX million in 2025 to XXX million by 2033, at a CAGR of XX% during the forecast period. The market growth is attributed to the increasing adoption of voice-based applications, such as voice assistants, voice-controlled devices, and interactive voice response (IVR) systems. Moreover, the growing demand for natural-sounding and human-like voice synthesis in the entertainment industry, e-commerce, and healthcare sectors is fueling market expansion. The advancements in deep learning and artificial intelligence (AI) are enabling the development of more sophisticated and accurate voice synthesis models, which is further driving market growth. However, the high cost of data collection and annotation, as well as concerns over privacy and data security, pose challenges to the market. Voice synthesis data service is a rapidly growing market that is expected to be worth billions of dollars in the next few years. This growth is being driven by the increasing demand for voice-based applications, such as voice assistants, multimedia content creation, and language learning. Voice synthesis data is essential for training voice synthesis models, which are the computer programs that generate synthetic speech. The quality of the voice synthesis data directly affects the quality of the synthetic speech. There are a number of companies that provide voice synthesis data services. These companies collect and curate voice recordings from a variety of sources, including native speakers, professional voice actors, and amateurs. The voice synthesis data service market is expected to continue to grow rapidly in the coming years. This growth is being driven by the increasing demand for voice-based applications, as well as the advances in voice synthesis technology.

Introduction

This Czech 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 Czech -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 Czech 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.

Topic Diversity

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

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.

Metadata

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

Usage and Applications

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

Introduction

This Bahasa Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Bahasa-speaking customers. Featuring over 40 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.

Speech Data

The dataset contains 40 hours of dual-channel call center recordings between native Bahasa speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.

This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making financial domain model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

Introduction

This Mandarin Chinese Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Mandarin-speaking customers. Featuring over 30 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Mandarin Chinese speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.

This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making financial domain model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

High-quality English call center speech dataset for home services. Ideal for AI training, speech analytics, and customer service automation.

The global speech and audio data market is experiencing robust growth, driven by the increasing adoption of voice assistants, virtual assistants, and AI-powered applications across various sectors. The market, currently estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 20% from 2025 to 2033. This significant expansion is fueled by several factors, including advancements in natural language processing (NLP), the proliferation of connected devices (IoT), and the rising demand for personalized user experiences. The market's segmentation encompasses various applications, such as transcription services, speech analytics, voice biometrics, and voice search, each contributing to the overall market's momentum. Major players, including Google, Amazon, and Microsoft, are actively investing in research and development, leading to continuous innovation and market expansion. Challenges remain, such as data privacy concerns and the need for robust data security measures, but the overall market outlook remains highly positive. The growth trajectory of the speech and audio data market is expected to remain strong throughout the forecast period. Factors like the increasing penetration of smartphones and smart speakers, coupled with the growing adoption of cloud-based speech recognition technologies, will further propel market growth. The increasing need for efficient and accurate transcription services across various industries, including healthcare, legal, and media, is another significant driver. While regional variations in market penetration exist, North America and Europe currently dominate the market share. However, the Asia-Pacific region is expected to showcase substantial growth in the coming years, driven by rising digitalization and increasing smartphone adoption in emerging economies. The competitive landscape is characterized by the presence of both established tech giants and specialized speech technology providers, fostering innovation and providing diverse solutions to meet the evolving market needs.