A suite of AI metrics that can be used to measure and track the performance of the task-specific models.

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Explore our innovative AI solutions that empower seamless communication and drive progress in the field of speech technology.

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Key Tasks in NLP and Speech Technology

Explore the core functions that enhance communication through language understanding, translation, and speech recognition.

  • Machine translation (MT)

    Converts text from one language to another, maintaining the meaning and context of the original message. This task involves translating between languages like English to French or Polish to Spanish and aims to ensure both grammatical and semantic accuracy.

  • Automatic Speech Recognition (ASR)

    Converts spoken language into written text by processing audio inputs. ASR systems are widely used in applications like transcription, virtual assistants, and speech-to-text services.

  • Speech Translation (ST)

    Converts spoken language from one language into spoken or written output in another language in real time or offline. This task combines ASR, machine translation, and TTS to facilitate seamless communication across language barriers, often used in live conversations, broadcasts, or conferences.

  • Speech Sumarization (SSUM)

    Produces summaries directly from spoken content, such as meetings or lectures, eliminating the need for full transcription and helping users quickly grasp key points from audio sources.

  • Speech Question-Anwering (SQA)

    Enables interactive systems to answer questions based on spoken inputs or audio sources, combining ASR with natural language understanding to deliver accurate, real-time responses.

  • Spoken Language Understanding (SLU)

    Analyzes spoken language to extract meaning, intents, or commands. SLU powers voice assistants and dialogue systems by interpreting user speech for appropriate action or response.

  • Lip Reading (LIPREAD)

    Recognizes spoken words by analyzing lip movements in video inputs, useful in noisy environments or for accessibility purposes, such as assisting hearing-impaired individuals.

  • Text-to-Speech (TTS)

    Converts written text into natural-sounding speech, facilitating applications like audiobooks, virtual assistants, and accessibility tools for visually impaired users.

  • Lip Generation (LIPGEN)

    Synthesizes realistic lip movements synchronized with audio, typically used in animated characters, dubbing, or virtual avatars to improve the realism of human-computer interaction.

  • Sumarization (SUM)

    Summarization is the task of generating concise versions of longer texts while preserving the most important information and main ideas. It can be either extractive (selecting key sentences) or abstractive (creating new sentences).

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Our leaderboards cover a wide range of tasks, from speech translation to text generation and beyond, offering detailed comparisons of models tested across various datasets and language pairs. With rankings based on performance metrics like BLEU, CHRF, TER, and more, you can easily find the model that meets your specific requirements.

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