Definition of greedy decoder

[inchpunch]

I am wondering where can I find the definition of greedy decoder? I saw on

https://nvidia.github.io/OpenSeq2Seq/html/speech-recognition.html#speech-recognition

it says "WER is the word error rate obtained on a dev-clean subset of LibriSpeech using greedy decoder (decoder_params/use_language_model = False). "

For the reference WERs on that page, except not using LM, does greedy decoder use the beam size of 512 as specified in the configuration file given by the links?

Thanks a lot!

[bill-kalog]

Probably someone from the team maintaining openSeq2Seq would be more appropriate to answer because they are doing changes at the moment to accommodate for extracting timesteps from the decoding too. For example here https://github.com/NVIDIA/OpenSeq2Seq/blob/1a58b2a563ce46a3ed87075cfed6bd6e008e49c8/open_seq2seq/utils/ctc_decoder.py But as your question goes, if I am not wrong, you can see which decoders are used in this file https://github.com/NVIDIA/OpenSeq2Seq/blob/1a58b2a563ce46a3ed87075cfed6bd6e008e49c8/open_seq2seq/decoders/fc_decoders.py#L247 So here I am pointing you to where the greedy decoder is and a few lines up you can see the language model decoder which calls the old lm_decoder mozilla deepspeech used to have in their repo. Here you can also see that the beam_width is only used when the call to the lm decoder is happening. If you want to do normal beam search (i.e not greedy with a tensorflow op) you can replace the tf.nn.ctc_greedy_decoder with tensorflows tf.nn.ctc_beam_search_decoder and give it your beam_width as an argument

[inchpunch]

Thanks for your information. I tried to do so, but WER gets much worse by using ctc_beam_search_decoder with beam width=1. The code that I modified in the fc_decoders.py is (starting line 240):

else:
  def decode_without_lm(logits, decoder_input, merge_repeated=True):
    if logits.dtype.base_dtype != tf.float32:
      logits = tf.cast(logits, tf.float32)
    # decoded, neg_sum_logits = tf.nn.ctc_greedy_decoder(
        # logits, decoder_input['encoder_output']['src_length'],
        # merge_repeated,
    # )
    decoded, neg_sum_logits = tf.nn.ctc_beam_search_decoder(
        logits, decoder_input['encoder_output']['src_length'],
        self.params['beam_width'], 1, merge_repeated,
    )
    return decoded

and in configuration file, in base_params I set

"decoder_params": {

    # params for decoding the sequence with language model
    "beam_width": 1,

Is there anything else that I missed?

[bill-kalog]

can you try with merge_repeated=False instead. merge_repeated seems to have a slightly different functionality between the two functions

[inchpunch]

Yes it works now. Thanks a lot.