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
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:
- 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.
Speech Data
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 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 Scripted & Spontaneous Speech
Two-person interaction, replicating real-world conversations and dialogues with multilingual exposure via dual-channel files and transcribed resources.
Group / Muti-party
Conversations
Multi-person discussions, capturing group dynamics, overlaps, and varied tones so as to accurately train speech models.
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 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 (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.
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.
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
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.
Reasons to choose Shaip as your Trustworthy Speech Data Collection Partner
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
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
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
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 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 Services
Now focus on computer vision along with NLP for training your models to identify objects, individuals, deterrents, and other visual elements to perfection
Recommended Resources
Offering
Audio Annotation for Intelligent AIs
Audio annotation services have been a forte of Shaip since the beginning. Develop, train & improve conversational AI, chatbots & speech recognition engines with our state-of-the-art audio annotation services.
Buyer’s Guide
Buyer’s Guide: Complete Guide to Conversational AI
The chatbot you conversed with runs on an advanced conversational AI system that is trained, tested, and built using tons of speech recognition datasets.
Data Catalog
Off-the-Shelf Speech Data Catalog & Licensing
There are a wide variety of common applications for speech data in AI projects. We offer you vast amounts of high-quality data ready for your voice recognition.
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
Frequently Asked Questions (FAQ)
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.