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stt/ru/vosk-model-ru-0.42.7z

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stt/ru/vosk-model-ru-0.42/README

@@ -0,0 +1,60 @@
+## Russian model for Vosk
+
+Copyright 2017-2050 AC Technologies LLC
+
+This is a Vosk model for Russian
+
+
+## Changes in version 0.42
+
+Extended vocabulary, retrained LM and RNNLM
+
+Our audiobooks    %WER   4.5
+Our calls         %WER  28.2
+Silero audiobooks %WER  11.1
+Silero calls      %WER  36.0
+Silero youtube    %WER  19.5
+Golos crowd       %WER   4.4
+Sova devices      %WER  17.9
+
+
+## Changes in version 0.22
+
+Multistream architecture, golos dataset (https://github.com/sberdevices/golos)
+
+Our audiobooks    %WER  5.74
+Our calls         %WER 30.60
+Silero audiobooks %WER 13.35
+Silero calls      %WER 37.38
+Silero youtube    %WER 20.73
+Golos crowd       %WER  8.65
+Sova devices      %WER 19.71
+
+
+## Changes in version 0.10
+
+No accuracy changes, reorganize layout to directly load the model from vosk-api
+
+Our audiobooks    %WER  6.49
+Our calls         %WER 36.24
+Silero audiobooks %WER 16.04
+Silero calls      %WER 40.69
+Silero youtube    %WER 26.81
+Golos crowd       %WER 28.87
+Sova devices      %WER 29.22
+
+
+## Changes in version 0.9
+
+Added RNNLM rescoring
+
+
+## Changes in version 0.8
+
+More data and augmentations, should be better on phone calls
+
+
+## Changes in version 0.7
+
+Bigger tdnn-f model with specaugment, more epochs
+Much better language model trained on huge amount of texts

stt/ru/vosk-model-ru-0.42/am/final.mdl

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stt/ru/vosk-model-ru-0.42/am/frame_subsampling_factor

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stt/ru/vosk-model-ru-0.42/am/tree

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stt/ru/vosk-model-ru-0.42/conf/ivector_extractor.conf

@@ -0,0 +1,6 @@
+--splice-config=ivector/splice.conf
+--cmvn-config=ivector/online_cmvn.conf
+--lda-matrix=ivector/final.mat
+--global-cmvn-stats=ivector/global_cmvn.stats
+--diag-ubm=ivector/final.dubm
+--ivector-extractor=ivector/final.ie

stt/ru/vosk-model-ru-0.42/conf/mfcc.conf

@@ -0,0 +1,7 @@
+--use-energy=false
+--num-mel-bins=40
+--num-ceps=40
+--low-freq=20
+--high-freq=7600
+--allow-upsample=true
+--allow-downsample=true

stt/ru/vosk-model-ru-0.42/conf/model.conf

@@ -0,0 +1,10 @@
+--min-active=200
+--max-active=7000
+--beam=13.0
+--lattice-beam=6.0
+--acoustic-scale=1.0
+--frame-subsampling-factor=3
+--endpoint.silence-phones=1:2:3:4:5:6:7:8:9:10
+--endpoint.rule2.min-trailing-silence=0.5
+--endpoint.rule3.min-trailing-silence=1.0
+--endpoint.rule4.min-trailing-silence=2.0

stt/ru/vosk-model-ru-0.42/conf/online.conf

@@ -0,0 +1,4 @@
+--feature-type=mfcc
+--mfcc-config=conf/mfcc.conf
+--ivector-extraction-config=conf/ivector_extractor.conf
+--endpoint.silence-phones=1:2:3:4:5:6:7:8:9:10

stt/ru/vosk-model-ru-0.42/decode.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python3
+
+from vosk import Model, KaldiRecognizer, SetLogLevel
+import sys
+import os
+import wave
+
+SetLogLevel(0)
+
+if len(sys.argv) == 2:
+    wf = wave.open(sys.argv[1], "rb")
+else:
+    wf = wave.open("decoder-test.wav", "rb")
+
+if wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getcomptype() != "NONE":
+    print ("Audio file must be WAV format mono PCM.")
+    exit (1)
+
+model = Model(".")
+rec = KaldiRecognizer(model, wf.getframerate())
+rec.SetWords(True)
+
+while True:
+    data = wf.readframes(4000)
+    if len(data) == 0:
+        break
+    if rec.AcceptWaveform(data):
+        print(rec.Result())
+    else:
+        print(rec.PartialResult())
+
+print(rec.FinalResult())

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stt/ru/vosk-model-ru-0.42/extra/README

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+Here are the corrected reference transcripts we use for WER tests

stt/ru/vosk-model-ru-0.42/graph/disambig_tid.int

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+9855
+9856
+9857
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stt/ru/vosk-model-ru-0.42/graph/num_pdfs

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+<eps> 0
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