Services | TECHNOLOGY
Speech AI
Speech AI enables computers and other devices to understand and reproduce human speech. Today the technology becomes more and more popular across many industries. It is used to build voice-enabled and speech processing applications, automate meeting transcriptions and many more.
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Voice activity detection (VAD)
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Key features:
A unique SaaS solution
Speech APIs are usually sold as a package with many functions at once, which makes it much more complex and expensive. However, at UniDataLab, we embrace flexibility and a customer-centric approach, so we are ready to deliver each module separately.
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Common use cases:
Customer support
Smart home / voice commands
Security
Case studies:
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Automatic speech recognition (speech-to-text)
Automatic speech recognition (ASR) is a technology that converts spoken language into text. It is used to transcribe audio recordings, enable voice commands in different languages or identify multiple speakers. ASR has already become the gateway to AI-driven interactive products and services like virtual assistants or smart devices.
Key features:
High accuracy
Our ASR applications are guaranteed to have an over 90% accuracy rate.
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Common use cases:
Assistive education technologies
Transcription of patient-doctor conversations
Voice commands/ smart devices
Virtual assistants
Case studies:
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Multilingual speech generation (text-to-speech)
This technology enables the generation of naturally sounding human-like voices using AI-based computer simulation. The content can be recreated in many languages with a variety of real human voices of different gender, age group, pitch, and other acoustically significant features.
Key features:
High accuracy
Our ASR applications are guaranteed to have an over 90% accuracy rate.
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Common use cases:
Voice assistants/chatbots
E-learning text-to-speech app
Call center automation
Content creation applications (voicing blogs, books, etc.)
Case studies:
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Voice transformation
The technology allows modification of a speaker's voice without impacting the text of the original recording. Such a transformation can be done in two ways: cloning and effects overlaying. It is often used to dub series, movies or games into another language, as well as to build a variety of translation applications.
Key features:
Fine-tuning on a small data sample
Just a small amount of data (a piece of voice recording) is enough for us to clone and reproduce a specific effect.
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Common use cases:
Translation applications for tourists
Voice dubbing
Game porting
Speech-enabled translator for doctor-patient interactions
Case studies:
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Speaker diarization and identification
This technology labels audio recordings with corresponding timestamps that define boundaries between different speakers. Each segment is associated with a particular speaker. Their gender or age can also be detected. Speaker diarization and identification are an important part of any speech analytics application.
Key features:
High accuracy
Our solutions have shown state-of-the-art results on generally accepted benchmark data sets.
Common use cases:
Media annotation
Automatic journaling
Speech analytics for call centers
Case studies:
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Pronunciation validation
This technology can analyze what you say and how you say it by focusing on sounds, not words. Besides speech analysis on a phoneme level, it includes an advanced scoring system on top, followed by detailed visualized feedback. This makes it not only a critical component of an ASR system but also a basis for building pronunciation applications.
Key features:
Multilingual support
Our solutions fully support 30+ languages
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Common use cases:
Language learning apps
Voice identification systems
Language therapy apps
Voice dubbing systems
Case studies:
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Speech-to-speech translation
As its name suggests, the technology translates speech from one language to another. It is an important part of many applications and has great business value. For example, speech-to-speech translation can be used for the creation of automatic translation of content or instant voice translation applications.
Key features:
High accuracy
Our solutions are guaranteed to have over 90% accuracy rate.
Common use cases:
Instant voice translator
Game porting
Speech-enabled translator for doctor-patient interactions
Voice dubbing
Case studies:
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Sound analysis & classification
Sound analysis is aimed at analyzing and understanding audio signals captured by digital devices. Sound classification assigns a label or class to a given audio. The combination of the two technologies has countless business applications. For example, they are used to enable sound recognition, extraction of background noises, and side sounds and emotion recognition.
Key features:
No other similar SaaS solutions
The solution is built to solve a specific problem (while other vendors only provide it in a package. Plus, it is highly customizable (we can easily add new sounds, classes and categories).
Common use cases:
Medical sound analysis (e.g. respiratory analysis)
Emotion recognition systems
Smart home devices
Automated manufacturing
Case studies:
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Echo and noise cancellation
As the name suggests, the technology can eliminate background noises and echoes from your microphone and speaker or from a video. The business value of echo and noise cancellation is clear: it can ensure distraction-free calls or be used in video editing.
Key features:
High accuracy
Our solutions are guaranteed to have over 90% accuracy rate.
Common use cases:
Voice-removing software for video calls
Voice dubbing
Voice identification applications
Improved hearing aid device
Case studies:
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