Speech, language and applied intelligence
Reach French- and Arabic-speaking users with useful, evaluated speech and language experiences.
Develop language interaction around a defined user task. Our work includes French and Arabic speech recognition, multilingual experiences and Quran recitation practice, with evaluation and user control.
Speech, language and applied intelligence
Our language work includes French and Arabic speech recognition, spoken interaction, multilingual interfaces and Quran recitation practice. These capabilities bring together language processing, structured content and synchronized media.
Machine learning and generative AI can support interaction and task assistance, alongside deterministic logic for constraints, validation and workflow control. Define the role of each method, evaluate its behavior and keep users in control of sensitive actions.
On-device and connected processing are considered against privacy, latency, model availability and device resources. Product-specific features and release status are described on the relevant product pages.
Speech interaction requires attention to more than transcription. Language selection, recognition availability, microphone permissions, interruptions and correction workflows affect whether the feature is useful. French and Arabic introduce different linguistic and interface considerations; Arabic applications also require correct handling of right-to-left text and mixed-direction content.
In recitation and learning experiences, recognized speech must be related to structured source material and presented as understandable practice feedback. Text, page views, audio and user progress need consistent reference points. Users need a clear way to review recognition results and recover when the system cannot confidently interpret what was said.
Applied AI is evaluated within a defined task. We consider what information the model receives, which outputs are acceptable, how results are checked and which actions require explicit user control. Deterministic workflows provide stable constraints around probabilistic capabilities. Evaluation covers ordinary use, incorrect output, unavailable models and the resources required on supported devices.