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SoundHound’s ASR delivers higher sentence accuracy through our Speech-to-Meaning® technology and a richer context for recognizing words. The integration of our NLU components enables our neural network-based ASR to transcribe complex speech with greater precision.
BENEFITS
Our highly optimized, tunable, and scalable ASR engine supports vocabulary sizes containing millions of words. SoundHound’s machine learning infrastructure allows us to tune the engine to achieve optimal CPU performance, while delivering higher accuracy rates.
Our deep learning architecture uses sophisticated training methods in a variety of real-world scenarios—including different acoustic conditions, speaker variations, and application domains—for the highest accuracy.
Neural Network Language models integrated with elements of NLU allow our ASR to understand the context of the spoken word and deliver higher-quality statistical models in the presence of compound sentences—resulting in increased transcription accuracy.
Dynamically augment your ASR client to accurately understand your unique lexicon and deliver more accurate results. Simply upload grammars containing new phrases and vocabularies for instant augmentation.
Highly-accurate advanced acoustic models trained to perform in a variety of scenarios.
Optimize your voice-enabled products with connectivity options ranging from fully-embedded or hybrid to exclusively cloud-connected. Choose the solution that best fits your NLU requirements, CPU processing power, and privacy requirements.
Noisy environments present unique challenges for ASR. By augmenting our data with the unique characteristics of your user’s environment, such as ambient noise, multiple speakers, and echos, we are able to deliver ASR models with unprecedented accuracy.
SoundHound’s advanced voice AI transforms video calls and meetings into efficient, convenient, and hands-free experiences featuring highly-accurate transcription and speaker ID capabilities.
If you’re a multinational company or you may be one in the future, your voice assistant must speak more languages.
Our growing library of languages provides the data necessary to quickly train highly-accurate models for new languages. We currently support 25 of the world’s most popular languages with more in development.
Our acoustic models are exposed to robust training data that cover a wide range of subjects— from both native language and second language speakers—and include distinct regional models for large populations with known variations and accents.
Talk to us about how we can help bring your voice AI strategy to life.