Most Trusted Speech Data Collection Services for your AI

Train your NLP models, VAs, TTS prototypes, and more with quality conversational data, with our audio and speech data collection services

Speech data collection

Discover audio data pipelines without bottlenecks

Featured Clients

Professional Audio / Voice Data Collection Services

Any subject. Any scenario.

At Shaip, our expertise lies in creating high-quality speech datasets designed for varied AI/ML requirements. We offer an expansive range of languages and record in diverse settings making our datasets comprehensive and adaptable. Our focus is on feeding models with the highest volume of custom speech data, in the least possible time. With us on board, you can expect: 

Speech collection
  • Curated high-quality multilingual audio / voice data to improve accuracy
  • Highest possible level of domain specificity to target diverse scenario setup
  • Scale your ML model to suit diverse demographics and verticals
  • Recording Environments: Studio Quality, featuring crystal-clear audio with minimal background noise, & Natural Environments, where recordings incorporate ambient sounds to mimic real-world situations.
Countries
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Hours of
Speech Data
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Projects
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Languages (100+ Dialects)
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8/16/44/48 kHz

Sampling rate

Our Expertise

Align Audio Data to for Smarter NLP Models

Shaip offers end-to-end speech/audio data collection services in over 100+ languages to enable voice-enabled technologies to cater to a diverse set of audiences across the globe. We can work on projects of any scope and size; from licensing existing off-the-shelf audio datasets, to managing custom audio data collection, to audio transcription and annotation. No matter how big is your speech data collection project, we can customize the audio collection services to suit your needs to build high-quality NLP datasets that target dialects, tones, and languages. Choose from our wide range of speech datasets and audio data collection resources, for voice-enabling intelligent setups.

Monologue speech

Monologue Scripted & Spontaneous Speech

It focuses on processing speech from a single speaker. Utilize scripted prompts to feed into single-channel audio files, ensuring the capture of unique speech patterns, tones, and nuances specific to that individual.

Dialogue speech

Dialogue Scripted & Spontaneous Speech

Two-person interaction, replicating real-world conversations and dialogues with multilingual exposure via dual-channel files and transcribed resources.

Multi-party conversations

Group / Muti-party
Conversations

Multi-person discussions, capturing group dynamics, overlaps, and varied tones so as to accurately train speech models.

Wake-word utterances collection

Wake-word / Key Phrase / Utterances Collection​

Train AIs to identify key phrases or wake words or utterances with similar meanings using diverse, rich, and authentic utterances for advanced natural language processing and understanding.

Acoustic speech

Acoustic Data
Collection

We can professionally record studio-quality audio data be it restaurants, offices, or homes or from various environments and languages, whilst covering a wider acoustic range (Comprehensive Sound Datasets).

Automatic speech recognition

Automatic Speech Recognition (ASR)

Improve accuracy of your automatic speech recognition (ASR) systems by having access to state-of-art diversified speech/audio datasets, from a wide array of demographics.

Natural language utterance

Multilingual Speech/Audio Training Data

Our skilled language professionals, across the globe offer multilingual audio/speech data in various languages and dialects. This effort fosters global communication and bridges language barriers, contributing to more inclusive and effective AI solutions.

Digital virtual assistants

Text-to-Speech
(TTS)

Build a text-to-speech (TTS) multilingual model with the help of our global workforce, who help you collect speech data in 150+ languages & dialects to enhance your AI models from in-car controls to chatbots and learning solutions with high-quality audio data.

Call center recordings

Call Center
Conversations

Genuine exchanges between agents and clients, supporting numerous languages such as Spanish, German, American English, Bengali, Japanese, Chinese, and Hindi.

Success Stories

Conversational AI datasets with over 3k hours of data across 8 languages

Looking to build a multilingual platform for Indian languages, the client partnered with Shaip to collect, segment and transcribe large datasets in multiple Indian languages. This would help develop effective speech models that could power the client’s innovative new platform.

Problem: Over 3,000 hours of audio data collected in 8 Indian languages, segmented and transcribed to develop automatic speech recognition.

Solution: We provided data collection, segmentation, transcription, and delivered JSON files with metadata. We collected 3000 hours of audio data in 8 Indian languages at scale for the client’s speech technology project.

Speech data collection case study

Reasons to choose Shaip as your Trustworthy Speech Data Collection Partner

People

People

Dedicated and trained teams:

  • 30,000+ collaborators for Data Creation, Labeling & QA
  • Credentialed Project Management Team
  • Experienced Product Development Team
  • Talent Pool Sourcing & Onboarding Team
Process

Process

Highest process efficiency is assured with:

  • Robust 6 Sigma Stage-Gate Process
  • A dedicated team of 6 Sigma black belts – Key process owners & Quality compliance
  • Continuous Improvement & Feedback Loop
Platform

Platform

The patented platform offers benefits:

  • Web-based end-to-end platform
  • Impeccable Quality
  • Faster TAT
  • Seamless Delivery

Off-the-Shelf Speech / Audio Datasets

Services Offered

Expert text data collection isn’t all-hands-on-deck for comprehensive AI setups. At Shaip, you can even consider the following services to make models way more widespread than usual:

Text data collection

Text Data Collection
Services

The true value of Shaip cognitive data collection services is that it gives organizations the key to unlock critical information found within unstructured data

Image data collection

Image Data Collection Services

Make sure that your computer vision model identifies every image accurately, to seamlessly train next-gen AI models of the future

Video data collection

Video Data Collection Services

Now focus on computer vision along with NLP for training your models to identify objects, individuals, deterrents, and other visual elements to perfection

Shaip contact us

Want to build your own audio dataset?

Connect with our in-house speech data collection expert to set up an audio repository that best fits your requirement

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Speech Data Collection for an ML Model refers to the process of gathering audio recordings of spoken language. This collection aids in training and refining machine learning algorithms, particularly those centered on understanding and processing human voices.

When aiming to collect audio data for Automatic Speech Recognition (ASR), you should start by defining your project’s specific needs, including the desired language, accent, and type of speech. After setting these parameters, ensure you obtain all necessary permissions to respect user privacy. Then, use appropriate recording devices or software to capture clear audio samples. Each recording should be meticulously annotated with its transcription or other pertinent metadata and stored systematically for effortless access.

A speech dataset in machine learning is pivotal for training, testing, and validating models tailored to recognize, transcribe, or interpret spoken language. Such datasets pave the way for a myriad of applications, from voice assistants and transcription services to voice biometrics.

For collecting precise data from diverse languages and accents, collaboration with native speakers of the desired linguistic backgrounds is vital. Aim for a varied and representative sample to cover a broad spectrum of demographic nuances. Employ standardized recording equipment in uniform environments to ensure audio consistency. And importantly, annotate each data piece with detailed transcriptions and metadata, denoting the specific language and accent.