text: Title: SingleUtteranceGmmDecoder.feature_pipeline() causes segmentation fault
  Body: Kaldi:  compiled from master (d366a93aad)
  PyKaldi: pykaldi-cpu 0.1.3 py37h14c3975_1 pykaldi
  Python: 3.7.11
  OS: Manjaro Linux VM
  
  When calling `feature_pipeline()` from a `SingleUtteranceGmmDecoder` object twice, a segmentation fault occurs.
  
  I am trying to run online GMM based decoding. I translated a similar c++ example that can be found here: <https://kaldi-asr.org/doc/online_decoding.html#GMM-based>, to PyKaldi. But when I try to feed the `OnlineFeaturePipeline` instance with audio data, it crashes with a segmentation fault. 
  
  I could enclose the error to being thrown when trying to get the feature pipeline twice and created following minimal working example:
  
  ```py
  #!/usr/bin/env python
  
  from kaldi.online2 import (
      SingleUtteranceGmmDecoder,
      OnlineGmmAdaptationState,
      OnlineFeaturePipelineCommandLineConfig,
      OnlineGmmDecodingConfig,
      OnlineFeaturePipelineConfig,
      OnlineFeaturePipeline,
      OnlineGmmDecodingModels,
  )
  from kaldi.fstext import read_fst_kaldi
  
  import subprocess, sys
  from os.path import expanduser
  
  base_path = expanduser("~/speech/kaldi/asr")
  kaldi_root = expanduser("~/speech/kaldi/kaldi")
  
  subprocess.run(
      f"{kaldi_root}/src/bin/matrix-sum --binary=false scp:{base_path}/data/train/cmvn.scp - >/tmp/global_cmvn.stats", shell=True
  )
  
  feature_cmdline_config = OnlineFeaturePipelineCommandLineConfig()
  feature_cmdline_config.feature_type = "mfcc"
  feature_cmdline_config.mfcc_config = f"{base_path}/conf/mfcc.conf"
  feature_cmdline_config.global_cmvn_stats_rxfilename = "/tmp/global_cmvn.stats"
  feature_config = OnlineFeaturePipelineConfig.from_config(feature_cmdline_config)
  
  decode_config = OnlineGmmDecodingConfig()
  decode_config.faster_decoder_opts.beam = 11.0
  decode_config.faster_decoder_opts.max_active = 7000
  decode_config.model_rxfilename = f"{base_path}/exp/mono/final.mdl"
  
  
  gmm_models = OnlineGmmDecodingModels(decode_config)
  pipeline_prototype = OnlineFeaturePipeline(feature_config)
  decode_fst = read_fst_kaldi(f"{base_path}/exp/mono/graph/HCLG.fst")
  adaptation_state = OnlineGmmAdaptationState()
  
  decoder = SingleUtteranceGmmDecoder(
      decode_config, gmm_models, pipeline_prototype, decode_fst, adaptation_state
  )
  
  # this one does not crash, but using pipe.accept_waveform crashed for me
  pipe = decoder.feature_pipeline()
  # the next line crashes with "segmentation fault (core dumped)"
  pipe = decoder.feature_pipeline()
  ```