Keith Vertanen の言語モデルの 1 つと組み合わせて、Android で PocketSphinx を使用して「ディクテーション」機能を実装しようとしています。サンプルを次のように変更しました。
private void setupRecognizer(File assetsDir) throws IOException {
recognizer = defaultSetup()
.setAcousticModel(new File(assetsDir, "en-us-ptm"))
.setDictionary(new File(assetsDir, "cmudict-en-us.dict"))
.setRawLogDir(assetsDir)
.setKeywordThreshold(1e-45f)
.setBoolean("-allphone_ci", true)
.getRecognizer();
recognizer.addListener(this);
File ngramModel = new File(assetsDir, "lm_csr_5k_nvp_2gram.arpa");
recognizer.addNgramSearch(NGRAM_SEARCH, ngramModel);
lm_csr_5k_nvp_2gram.arpaKeith Vertanen のサイトの 5K NVP 2-gram ダウンロードからの場所です 。
次のエラーが表示されます。
1 18:04:29.861 2837-2863/? I/SpeechRecognizer: Load N-gram model /storage/emulated/0/Android/data/edu.cmu.sphinx.pocketsphinx/files/sync/lm_csr_5k_nvp_2gram.arpa
01-31 18:04:29.861 2837-2863/? I/cmusphinx: INFO: ngram_model_trie.c(399): Trying to read LM in trie binary format
01-31 18:04:29.861 2837-2863/? I/cmusphinx: INFO: ngram_model_trie.c(410): Header doesn't match
01-31 18:04:29.861 2837-2863/? I/cmusphinx: INFO: ngram_model_trie.c(177): Trying to read LM in arpa format
01-31 18:04:29.862 2837-2863/? E/cmusphinx: ERROR: "ngram_model_trie.c", line 103: Bad ngram count
01-31 18:04:29.862 2837-2863/? I/cmusphinx: INFO: ngram_model_trie.c(489): Trying to read LM in DMP format
01-31 18:04:29.862 2837-2863/? E/cmusphinx: ERROR: "ngram_model_trie.c", line 500: Wrong magic header size number a5c6461: /storage/emulated/0/Android/data/edu.cmu.sphinx.pocketsphinx/files/sync/lm_csr_5k_nvp_2gram.arpa is not a dump file
01-31 18:04:29.864 2837-2863/? E/AndroidRuntime: FATAL EXCEPTION: AsyncTask #1
Process: edu.cmu.sphinx.pocketsphinx, PID: 2837
java.lang.RuntimeException: An error occurred while executing doInBackground()
at android.os.AsyncTask$3.done(AsyncTask.java:309)
at java.util.concurrent.FutureTask.finishCompletion(FutureTask.java:354)
at java.util.concurrent.FutureTask.setException(FutureTask.java:223)
at java.util.concurrent.FutureTask.run(FutureTask.java:242)
at android.os.AsyncTask$SerialExecutor$1.run(AsyncTask.java:234)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1113)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:588)
at java.lang.Thread.run(Thread.java:818)
Caused by: java.lang.RuntimeException: Decoder_setLmFile returned -1
at edu.cmu.pocketsphinx.PocketSphinxJNI.Decoder_setLmFile(Native Method)
at edu.cmu.pocketsphinx.Decoder.setLmFile(Decoder.java:172)
at edu.cmu.pocketsphinx.SpeechRecognizer.addNgramSearch(SpeechRecognizer.java:247)
at edu.cmu.pocketsphinx.demo.PocketSphinxActivity.setupRecognizer(PocketSphinxActivity.java:161)
at edu.cmu.pocketsphinx.demo.PocketSphinxActivity.access$000(PocketSphinxActivity.java:50)
at edu.cmu.pocketsphinx.demo.PocketSphinxActivity$1.doInBackground(PocketSphinxActivity.java:72)
at edu.cmu.pocketsphinx.demo.PocketSphinxActivity$1.doInBackground(PocketSphinxActivity.java:66)
at android.os.AsyncTask$2.call(AsyncTask.java:295)
at java.util.concurrent.FutureTask.run(FutureTask.java:237)
at android.os.AsyncTask$SerialExecutor$1.run(AsyncTask.java:234)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1113)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:588)
at java.lang.Thread.run(Thread.java:818)
台詞
01-31 18:04:29.861 2837-2863/? I/cmusphinx: INFO: ngram_model_trie.c(177): Trying to read LM in arpa format
01-31 18:04:29.862 2837-2863/? E/cmusphinx: ERROR: "ngram_model_trie.c", line 103: Bad ngram count
lm_csr_5k_nvp_2gram.arpaファイルが正しくフォーマットされていないか何かだと思います。ファイルは次のようになります。
\data\
ngram 1=5000
ngram 2=4331397
ngram 3=0
\1-grams:
-2.11154 </s> 0
-99 <s> -3.13167
-0.3954594 <unk> -0.4365645
-2.271447 a -2.953606
-3.384721 a. -1.85196
-5.788997 a.'s -0.8137056
-4.139672 abandoned -0.9728376
-3.904189 ability -1.838658
-4.360272 able -2.161723
...
これは、少なくともサンプル ファイルのように見えます。
私の他の唯一の考えは、おそらく拡張子が間違っているということでした。
言語モデルは、テキスト ARPA 形式、バイナリ形式 BIN、バイナリ DMP 形式の 3 つの異なる形式で保存およびロードできます。ARPA フォーマットはより多くのスペースを必要としますが、編集することは可能です。ARPA ファイルの拡張子は .lm です。バイナリ形式は、スペースが大幅に少なくて済み、読み込みが高速です。バイナリ ファイルの拡張子は .lm.bin です。フォーマット間の変換も可能です。DMP 形式は廃止され、推奨されません。
lm_csr_5k_nvp_2gram.lmこれにより、ファイルの名前を の代わりに付ける必要があるように聞こえますlm_csr_5k_nvp_2gram.arpa。ただし、例外を変更することなく、ファイルの名前を変更しようとしました。
これを行う正しい方法は何ですか？