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Think-A-Move SPEAR Speech Recognition

✓ Think-A-Move SPEAR Speech Recognition

SPEAR Speech Recognition delivers robust voice command and transcription in high-noise environments for mobile and fixed devices.

About ✓ Think-A-Move SPEAR Speech Recognition

SPEAR is a fully embedded speech recognition solution designed for Linux, Windows, and Android platforms. It excels in noisy conditions, offering both command recognition and free-form transcription. When paired with TAM’s in-ear voice capture earpiece, it achieves industry-leading accuracy.

Key features

Noise-robust DNN-Based Acoustic Model

Advanced deep neural network model for accurate speech recognition in noisy environments.

Noise-robust DNN-Based VAD Model

Deep neural network voice activity detection optimized for high-noise scenarios.

Domain-specific Language Model

Customizable language models tailored to specific industry or application needs.

Works Offline

Fully functional without internet connectivity for secure and reliable operation.

Supports NBest results

Provides multiple transcription alternatives for improved accuracy and context.

Supports Command and Control Applications

Enables voice-driven control systems with finite state grammar support.

Supports Transcriptions

Delivers statistical speech-to-text transcription for various applications.

Speaker Independent

Recognizes speech from any user without prior training or enrollment.

Grammar switching at runtime

Dynamically adjusts grammar rules during operation for flexibility.

Dynamic grammar compilation

Compiles grammar rules on-the-fly for real-time adaptability.

Supports 16K Audio Sampling Rate

Compatible with 16KHz audio input for high-fidelity speech processing.

Down-sample to 8K or 16K

Adjusts audio sampling rate to 8K or 16K for optimized performance.

Low CPU consumption Wake-up Word

Efficient wake-word detection with minimal processing power usage.

Floating point version

Available in floating-point precision for enhanced accuracy in demanding scenarios.

Barge-in support

Allows users to interrupt ongoing speech input for seamless interaction.

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