From 636e67b34729983b2d90591c01f2e820fe3955ae Mon Sep 17 00:00:00 2001
From: Wannaphong Phatthiyaphaibun <wannaphong@yahoo.com>
Date: Thu, 11 Aug 2022 16:43:50 +0700
Subject: [PATCH] PyThaiASR v1.1.0

- remove tokenized
---
 README.md             |  3 +--
 pythaiasr/__init__.py | 14 +++++---------
 setup.py              |  2 +-
 3 files changed, 7 insertions(+), 12 deletions(-)

diff --git a/README.md b/README.md
index 32a259f..c13358a 100644
--- a/README.md
+++ b/README.md
@@ -37,11 +37,10 @@ print(asr(file))
 ### API
 
 ```python
-asr(file: str, show_pad: bool = False, model: str = "airesearch/wav2vec2-large-xlsr-53-th")
+asr(file: str, model: str = "airesearch/wav2vec2-large-xlsr-53-th")
 ```
 
 - file: path of sound file
-- show_pad: show [PAD] in output
 - model: The ASR model
 - return: thai text from ASR
 
diff --git a/pythaiasr/__init__.py b/pythaiasr/__init__.py
index fce4242..9bac88c 100644
--- a/pythaiasr/__init__.py
+++ b/pythaiasr/__init__.py
@@ -19,6 +19,7 @@ def __init__(self, model: str="airesearch/wav2vec2-large-xlsr-53-th", device=Non
             * *wannaphong/wav2vec2-large-xlsr-53-th-cv8-deepcut* - Thai Wav2Vec2 with CommonVoice V8 (deepcut tokenizer) + language model 
         """
         self.processor = AutoProcessor.from_pretrained(model)
+        self.model_name = model
         self.model = AutoModelForCTC.from_pretrained(model)
         if device!=None:
             self.device = torch.device(device)
@@ -40,10 +41,9 @@ def prepare_dataset(self, batch: dict) -> dict:
         batch["input_values"] = self.processor(batch["speech"], sampling_rate=batch["sampling_rate"]).input_values
         return batch
     
-    def __call__(self, file: str, tokenized: bool = False) -> str:
+    def __call__(self, file: str) -> str:
         """
         :param str file: path of sound file
-        :param bool show_pad: show [PAD] in output
         :param str model: The ASR model
         """
         b = {}
@@ -53,20 +53,16 @@ def __call__(self, file: str, tokenized: bool = False) -> str:
         logits = self.model(input_dict.input_values).logits
         pred_ids = torch.argmax(logits, dim=-1)[0]
 
-        if tokenized:
-            txt = self.processor.batch_decode(logits.detach().numpy()).text
-        else:
-            txt = self.processor.batch_decode(logits.detach().numpy()).text.replace(' ','')
+        txt = self.processor.batch_decode(logits.detach().numpy()).text[0]
         return txt
 
 _model_name = "airesearch/wav2vec2-large-xlsr-53-th"
 _model = None
 
 
-def asr(file: str, tokenized: bool = False, model: str = _model_name) -> str:
+def asr(file: str, model: str = _model_name) -> str:
     """
     :param str file: path of sound file
-    :param bool show_pad: show [PAD] in output
     :param str model: The ASR model
     :return: thai text from ASR
     :rtype: str
@@ -81,4 +77,4 @@ def asr(file: str, tokenized: bool = False, model: str = _model_name) -> str:
         _model = ASR(model)
         _model_name = model
 
-    return _model(file=file, tokenized=tokenized)
+    return _model(file=file)
diff --git a/setup.py b/setup.py
index db394ea..50e533e 100644
--- a/setup.py
+++ b/setup.py
@@ -27,7 +27,7 @@ def read(*paths):
 
 setup(
 	name='pythaiasr',
-	version='1.0.1',
+	version='1.1.0',
 	packages=['pythaiasr'],
 	url='https://github.com/pythainlp/pythaiasr',
 	license='Apache Software License 2.0',