Incede's resources are experts in helping organizations understand and incorporate IBM’s watsonx technology and its generative AI models. We provide end-to-end capabilities in developing conversational interfaces and cognitive enterprise search applications with IBM watsonx platform.


When competitive advantage requires Generative AI and machine learning in your applications, Incede has the expertise.

Incede infuses watsonx foundation models and machine learning capabilities into applications for a deeper user experience and richer insights for decision-makers. For example, Incede solutions could integrate a conversational AI solution where a user provides a question in any number of natural languages, including speech, and shares a photo that is then evaluated and answered with the context of the user’s order history, sentiment, inquiry and specifics about their photo – in their preferred language, including voice.


Speech to Text

Speech to text uses customizable speech recognition to generate text transcripts in real-time or batch.

Incede develops and trains language models to understand and recognize domain specifics, jargons, dialects and expressions in audio and voice natural language.

case study

Lingmo Case Study

  • Accurate, nuanced, real-time translation services.
  • More than the gist; understand the full context of a conversation.
  • Boosts responsiveness to user feedback and enhances quality.

Powerful speech recognition

Customized speech-to-text capabilities, driven by machine learning, let customers ask their questions in natural language – fast-tracking them to the answer. You can also blend texting and voice simultaneously for instant information exchange by connecting Watson Speech to Text with watsonx Assistant over the phone.

Advanced Machine Learning

Speech to Text service relies on two key modeling capabilities: language modeling, that leverages a neural network-based language model to generate training text and acoustic modeling, that uses a fairly compact model to accommodate the resource limitations of the cloud. To train this compact model, IBM uses "teacher-student training / knowledge distillation." Large and strong neural networks such as Long Short-Term Memory (LSTM), VGG, and the Residual Network (ResNet) are first trained. The output of these networks is then used as teacher signals to train a compact model for actual deployment.

Automatically transcribes proper nouns and context-specific formatting

Speech-to-Text is tailored to work well with real-life speech and can accurately transcribe your audio in real-time or via uploaded batch files using any of our available out-of-the-box language models, audio frequency options and transcription output features. Format and organize your transcripts as you need by using features such as speaker labels, smart formatting, keyword spotting, numeric redaction, word timestamps, confidence and alternatives.

Hands-on speech training capabilities

Improve accuracy for your use case, especially around domain-specific terminology, acronyms, names, jargons, expressions, dialects and acoustical

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