Custom speech graphs

OneSpeech.Custom.GraphSpeechRecognizer is a low-level SpeechRecognizer for caller-supplied float32 ONNX or OneModel files. It never downloads or converts weights. The caller supplies lawful provenance in ModelInfo and an immutable TokenVocabulary, including a blank ID. Built-in family loaders remain the simpler choice for supported checkpoints.

Encoder contract

Each EncoderGraph has exactly one float32 input and output, batch one. Inputs are [1, channels, frames]. Intermediate outputs and transducer encoder outputs are channel-major. The final CTC output is [1, frames, vocabularySize], raw logits, including blank. Stages can split large encoders at layer boundaries. Declared batch, ranks and channel dimensions are checked at load; output sizes and temporal stride are checked at execution. Violations throw InvalidModelShapeException. File/format errors remain OneModel's load errors.

Front ends accept finite mono 16000 Hz PCM:

• RawWaveform: unchanged [1,1,samples]; no normalization is inferred.
• Whisper80 / Whisper128: unpadded log-mel, samples / 160 frames.
• Nemo128: NeMo normalized mel, with the masked trailing STFT frame cropped.

For each stage, frames become floor((frames - receptiveField) / stride) + 1, or ceil(frames / stride) when SamePadding is true. The caller specifies the final frameDuration in audio time. For omniASR, use raw waveform, receptive field 400, stride 320, 9812 output channels, blank 0 and 20 ms. For the split Parakeet encoder, use NeMo128, 1024 channels at both stages, first-stage stride 8 with same padding, then stride 1, blank 8192 and 80 ms.

Calls below 400 samples produce no words. Calls over 30 seconds use Silero VAD-first chunks; TranscribeStream yields immutable final segments from those chunks. Language hints are output labels, not acoustic conditioning or language identification. No translation or phrase-biasing head is inferred.

Search and vocabulary

CTC uses greedy collapse by default; beamSize 1–64 enables prefix beam for vocabularies up to 4096 IDs. Beam tokens are timed with our CTC Viterbi trellis; greedy tokens retain their occupied frame intervals. A failed beam alignment throws rather than inventing word timings. Confidence is the mean conditional token probability over its occupied frames, not a calibrated word posterior.

Vocabulary pieces concatenate without normalization. Optional metaspace decoding replaces U+2581 with space and removes one leading space. The caller supplies special-token surfaces (including an empty blank surface), and any unknown-token surface; byte-fallback decoding is not inferred. Pieces must not encode multiple whitespace-separated words in a single token: disjoint token ranges are required for word timing. Optional trailing-punctuation exclusion matches native transducer timing without changing written text. All words carry Native timing provenance, null confidence/times for a zero-token range, and initially Unassigned speaker. Times are clipped to the input horizon.

Packed transducer contract

TransducerGraphs declares separate predictor and joint files. The predictor maps [1,stateSize] to the same shape. Its zero state is run once to prime the blank input. On each accepted token, the first embeddingSize state values are replaced by that token's row in the caller-supplied embedding table, then run again. The first embeddingSize output values feed the joint after the current encoder frame. Remaining state values carry recurrent state.

The joint maps [1,encoderChannels + embeddingSize] to [1,vocabularySize + durationCount]. Empty durations select RNN-T greedy; strictly increasing durations beginning at zero select TDT greedy. Token logits precede duration logits. Default packed widths (640/3200), duration table [0,1,2,3,4], and 8193 embedding rows describe the converted Parakeet graph. Other predictor/state layouts need an adapted graph, not an implicit shim. All calls are synchronous, cancellation-aware at graph/search steps, and not thread-safe; dispose the recognizer to release its owned sessions.

Language hints are never an implicit capability: declare the supported language labels with the languages constructor argument on GraphSpeechRecognizer, for example languages: ["en", "fr"]. The default is empty (no hints accepted). Hints normalize through the shared rule and label output; this adapter has no language-conditioning or detection head. An undeclared hint throws CapabilityNotSupportedException instead of being silently treated as supported.