// online2/online-nnet3-decoding.h

// Copyright 2014 Johns Hopkins University (author: Daniel Povey)

// 2016 Api.ai (Author: Ilya Platonov)

// See ../../COPYING for clarification regarding multiple authors

//

// Licensed under the Apache License, Version 2.0 (the "License");

// you may not use this file except in compliance with the License.

// You may obtain a copy of the License at

//

// http://www.apache.org/licenses/LICENSE-2.0

//

// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY

// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED

// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,

// MERCHANTABLITY OR NON-INFRINGEMENT.

// See the Apache 2 License for the specific language governing permissions and

// limitations under the License.

#ifndef KALDI_ONLINE2_ONLINE_NNET3_DECODING_H_

#define KALDI_ONLINE2_ONLINE_NNET3_DECODING_H_

#include <string>

#include <vector>

#include <deque>

#include "nnet3/decodable-online-looped.h"

#include "matrix/matrix-lib.h"

#include "util/common-utils.h"

#include "base/kaldi-error.h"

#include "itf/online-feature-itf.h"

#include "online2/online-endpoint.h"

#include "online2/online-nnet2-feature-pipeline.h"

#include "decoder/lattice-faster-online-decoder.h"

#include "hmm/transition-model.h"

#include "hmm/posterior.h"

namespace kaldi {

/// @addtogroup onlinedecoding OnlineDecoding

/// @{

/**

You will instantiate this class when you want to decode a single

utterance using the online-decoding setup for neural nets.

*/

class SingleUtteranceNnet3Decoder {

public:

// Constructor. The pointer 'features' is not being given to this class to own

// and deallocate, it is owned externally.

SingleUtteranceNnet3Decoder(const LatticeFasterDecoderConfig &decoder_opts,

const TransitionModel &trans_model,

const nnet3::DecodableNnetSimpleLoopedInfo &info,

const fst::Fst<fst::StdArc> &fst,

OnlineNnet2FeaturePipeline *features);

/// advance the decoding as far as we can.

void AdvanceDecoding();

/// Finalizes the decoding. Cleans up and prunes remaining tokens, so the

/// GetLattice() call will return faster. You must not call this before

/// calling (TerminateDecoding() or InputIsFinished()) and then Wait().

void FinalizeDecoding();

int32 NumFramesDecoded() const;

/// Gets the lattice. The output lattice has any acoustic scaling in it

/// (which will typically be desirable in an online-decoding context); if you

/// want an un-scaled lattice, scale it using ScaleLattice() with the inverse

/// of the acoustic weight. "end_of_utterance" will be true if you want the

/// final-probs to be included.

void GetLattice(bool end_of_utterance,

CompactLattice *clat) const;

/// Outputs an FST corresponding to the single best path through the current

/// lattice. If "use_final_probs" is true AND we reached the final-state of

/// the graph then it will include those as final-probs, else it will treat

/// all final-probs as one.

void GetBestPath(bool end_of_utterance,

Lattice *best_path) const;

/// This function calls EndpointDetected from online-endpoint.h,

/// with the required arguments.

bool EndpointDetected(const OnlineEndpointConfig &config);

const LatticeFasterOnlineDecoder &Decoder() const { return decoder_; }

~SingleUtteranceNnet3Decoder() { }

private:

const LatticeFasterDecoderConfig &decoder_opts_;

// this is remembered from the constructor; it's ultimately

// derived from calling FrameShiftInSeconds() on the feature pipeline.

BaseFloat input_feature_frame_shift_in_seconds_;

// we need to keep a reference to the transition model around only because

// it's needed by the endpointing code.

const TransitionModel &trans_model_;

nnet3::DecodableAmNnetLoopedOnline decodable_;

LatticeFasterOnlineDecoder decoder_;

};

/// @} End of "addtogroup onlinedecoding"

} // namespace kaldi

#endif // KALDI_ONLINE2_ONLINE_NNET3_DECODING_H_