01
Streaming ASR
Continuous speech recognition converts incoming audio into incremental text with an emphasis on low latency and realistic speaking conditions.
RRHE APPLIED AI
Hybrid Streaming Translator.
Real-time spoken communication across languages.
Hybrid Streaming Translator is an RRHE research and product development project combining streaming speech recognition, machine translation and synthesized speech into a continuous low-latency conversation pipeline.
WORKING PROTOTYPE
The core pipeline is already operational.
The current prototype performs streaming speech recognition, translation and spoken output as one connected system.
Development is now focused on language expansion, recognition quality, latency, model optimization and deployment rather than proving the basic concept.
ARCHITECTURE
Built as a streaming language pipeline.
The system is designed around independent components that can be improved, replaced and optimized without rebuilding the entire product.
02
Translation Pipeline
Translation routes can use direct language models where appropriate or bridge unsupported language pairs through an intermediate language such as English.
03
Speech Output
Translated text is converted back into spoken output to keep the interaction conversational rather than text-only.
LANGUAGE ROUTING
We do not require a dedicated model for every language pair.
Where a high-quality direct translation model exists, the system can use it directly.
Where it does not, Hybrid Streaming Translator can bridge the conversation through another supported language. For example, Thai to Russian can be processed as Thai to English to Russian.
This approach reduces the number of dedicated models required while allowing the language network to expand progressively.
DEVELOPMENT STATUS
From prototype to language expansion.
The translator is functional today.
Current engineering work is concentrated on improving speech recognition, expanding language support, evaluating translation quality and preparing the mobile implementation for practical use.
English and Russian provide the existing development baseline. Thai is the first major additional language target for development and demonstration in Thailand.
CURRENT STATE
Core pipeline
Operational
Existing baseline
English · Russian
Next language focus
Thai
Processing model
Local + hybrid
Initial deployment
Mobile
CURRENT R&D
Focused model development and evaluation.
01
Multilingual speech-recognition adaptation
02
Thai ASR evaluation and optimization
03
Incremental translation quality
04
Streaming latency and segmentation
05
Model compression and mobile deployment
06
Controlled GPU training and evaluation
DEVELOPMENT INFRASTRUCTURE
Local development. Focused accelerated computing.
RRHE's local development server and GPU support baseline software engineering, dataset preparation, pipeline testing, model evaluation and deployment work.
Higher-performance accelerated computing supports larger-scale multilingual speech-recognition evaluation, Thai ASR optimization, translation-quality experiments, streaming latency and segmentation work, and model compression and optimization for mobile deployment.
Training datasets, configurations, checkpoints and evaluation results remain part of a persistent RRHE development pipeline; cloud compute is used as replaceable accelerated infrastructure.
PRODUCT DIRECTION
Mobile first.
Dedicated hardware later.
The first product implementation is being developed around mobile devices, allowing the complete translation experience to be tested and refined using readily available hardware.
The same technology can later support dedicated configurations for continuous hands-free translation and other environments where conventional mobile interaction is not ideal.