1. added deepgram support

2. compute asr sample accuracy

jasper/data/validation/process.py

@@ -156,6 +156,47 @@ def sample_ui(
     ExtendedPath(sample_path).write_json(processed_data)
 
 
+@app.command()
+def sample_asr_accuracy(
+    data_name: str = typer.Option(
+        "png_06_2020_week1_numbers_window_customer", show_default=True
+    ),
+    dump_dir: Path = Path("./data/asr_data"),
+    sample_file: Path = Path("sample_dump.json"),
+    asr_service: str = "deepgram",
+):
+    # import pandas as pd
+    # from pydub import AudioSegment
+    from ..utils import is_sub_sequence, Text2Num
+
+    # from ..utils import deepgram_transcribe_gen
+    #
+    # deepgram_transcriber = deepgram_transcribe_gen()
+    t2n = Text2Num()
+    # processed_data_path = dump_dir / Path(data_name) / dump_file
+    sample_path = dump_dir / Path(data_name) / sample_file
+    processed_data = ExtendedPath(sample_path).read_json()
+    # asr_data = []
+    match_count, total_samples = 0, len(processed_data["data"])
+    for dp in tqdm(processed_data["data"]):
+        # aud_data = Path(dp["audio_path"]).read_bytes()
+        # dgram_result = deepgram_transcriber(aud_data)
+        # dp["deepgram_asr"] = dgram_result
+        gcp_num = dp["text"]
+        dgm_num = t2n.convert(dp["deepgram_asr"].lower())
+        if is_sub_sequence(gcp_num, dgm_num):
+            match_count += 1
+            print(f"MATCH GCP:{gcp_num}\tDGM:{dgm_num}")
+        else:
+            print(f"FAIL GCP:{gcp_num}\tDGM:{dgm_num}")
+        # asr_data.append(dp)
+    typer.echo(
+        f"{match_count} from deepgram matches with {total_samples} gcp transcripts."
+    )
+    # processed_data["data"] = asr_data
+    # ExtendedPath(sample_path).write_json(processed_data)
+
+
 @app.command()
 def task_ui(
     data_name: str = typer.Option("call_upwork_train_cnd", show_default=True),
@@ -190,7 +231,9 @@ def dump_corrections(
     col = get_mongo_conn(col="asr_validation")
     task_id = [c for c in col.distinct("task_id") if c.rsplit("-", 1)[1] == task_uid][0]
     corrections = list(col.find({"type": "correction"}, projection={"_id": False}))
-    cursor_obj = col.find({"type": "correction", "task_id": task_id}, projection={"_id": False})
+    cursor_obj = col.find(
+        {"type": "correction", "task_id": task_id}, projection={"_id": False}
+    )
     corrections = [c for c in cursor_obj]
     ExtendedPath(dump_path).write_json(corrections)
 
@@ -271,7 +314,9 @@ def split_extract(
     dump_file: Path = Path("ui_dump.json"),
     manifest_file: Path = Path("manifest.json"),
     corrections_file: str = typer.Option("corrections.json", show_default=True),
-    conv_data_path: Path = typer.Option(Path("./data/conv_data.json"), show_default=True),
+    conv_data_path: Path = typer.Option(
+        Path("./data/conv_data.json"), show_default=True
+    ),
     extraction_type: ExtractionType = ExtractionType.all,
 ):
     import shutil
@@ -293,7 +338,9 @@ def split_extract(
         def extract_manifest(mg):
             for m in mg:
                 if m["text"] in extraction_vals:
-                    shutil.copy(m["audio_path"], dest_data_dir / Path(m["audio_filepath"]))
+                    shutil.copy(
+                        m["audio_path"], dest_data_dir / Path(m["audio_filepath"])
+                    )
                     yield m
 
         asr_manifest_writer(dest_manifest_path, extract_manifest(manifest_gen))
@@ -302,12 +349,14 @@ def split_extract(
         orig_ui_data = ExtendedPath(ui_data_path).read_json()
         ui_data = orig_ui_data["data"]
         file_ui_map = {Path(u["audio_filepath"]).stem: u for u in ui_data}
-        extracted_ui_data = list(filter(lambda u: u["text"] in extraction_vals, ui_data))
+        extracted_ui_data = list(
+            filter(lambda u: u["text"] in extraction_vals, ui_data)
+        )
         final_data = []
         for i, d in enumerate(extracted_ui_data):
-            d['real_idx'] = i
+            d["real_idx"] = i
             final_data.append(d)
-        orig_ui_data['data'] = final_data
+        orig_ui_data["data"] = final_data
         ExtendedPath(dest_ui_path).write_json(orig_ui_data)
 
         if corrections_file:
@@ -323,7 +372,7 @@ def split_extract(
             )
             ExtendedPath(dest_correction_path).write_json(extracted_corrections)
 
-    if extraction_type.value == 'all':
+    if extraction_type.value == "all":
         for ext_key in conv_data.keys():
             extract_data_of_type(ext_key)
     else:
@@ -345,7 +394,7 @@ def update_corrections(
 
     def correct_manifest(ui_dump_path, corrections_path):
         corrections = ExtendedPath(corrections_path).read_json()
-        ui_data = ExtendedPath(ui_dump_path).read_json()['data']
+        ui_data = ExtendedPath(ui_dump_path).read_json()["data"]
         correct_set = {
             c["code"] for c in corrections if c["value"]["status"] == "Correct"
         }
@@ -374,7 +423,9 @@ def update_corrections(
                     )
                 else:
                     orig_audio_path = Path(d["audio_path"])
-                    new_name = str(Path(tscript_uuid_fname(correct_text)).with_suffix(".wav"))
+                    new_name = str(
+                        Path(tscript_uuid_fname(correct_text)).with_suffix(".wav")
+                    )
                     new_audio_path = orig_audio_path.with_name(new_name)
                     orig_audio_path.replace(new_audio_path)
                     new_filepath = str(Path(d["audio_filepath"]).with_name(new_name))