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https://github.com/occ-ai/obs-localvocal
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refactor: Update timestamp variable name in transcription-filter-data.h (#109)
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845c1a813c
commit
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@ -465,8 +465,9 @@ int wmain(int argc, wchar_t *argv[])
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struct transcription_filter_audio_info info = {0};
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info.frames = frames; // number of frames in this packet
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// make a timestamp from the current position in the audio buffer
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info.timestamp = start_time + (int64_t)(((float)frames_count /
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(float)gf->sample_rate) *
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info.timestamp_offset_ns =
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start_time +
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(int64_t)(((float)frames_count / (float)gf->sample_rate) *
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1e9);
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circlebuf_push_back(&gf->info_buffer, &info, sizeof(info));
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}
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@ -489,7 +490,7 @@ int wmain(int argc, wchar_t *argv[])
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struct transcription_filter_audio_info info = {0};
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info.frames = frames; // number of frames in this packet
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// make a timestamp from the current frame count
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info.timestamp = frames_count * 1000 / gf->sample_rate;
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info.timestamp_offset_ns = frames_count * 1000 / gf->sample_rate;
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circlebuf_push_back(&gf->info_buffer, &info, sizeof(info));
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}
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@ -127,7 +127,7 @@ struct transcription_filter_data {
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// Audio packet info
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struct transcription_filter_audio_info {
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uint32_t frames;
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uint64_t timestamp; // absolute (since epoch) timestamp in ns
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uint64_t timestamp_offset_ns; // offset (since start of processing) timestamp in ns
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};
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// Callback sent when the transcription has a new result
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@ -103,7 +103,13 @@ struct obs_audio_data *transcription_filter_filter_audio(void *data, struct obs_
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// push audio packet info (timestamp/frame count) to info circlebuf
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struct transcription_filter_audio_info info = {0};
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info.frames = audio->frames; // number of frames in this packet
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info.timestamp = audio->timestamp; // timestamp of this packet
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// check if the timestamp is a false "negative" value for uint64_t
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if (audio->timestamp > (std::numeric_limits<uint64_t>::max() - 100000000)) {
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// set the timestamp to the current time
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info.timestamp_offset_ns = 0;
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} else {
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info.timestamp_offset_ns = audio->timestamp; // timestamp of this packet
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}
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circlebuf_push_back(&gf->info_buffer, &info, sizeof(info));
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}
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@ -22,24 +22,10 @@
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struct vad_state {
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bool vad_on;
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uint64_t start_timestamp;
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uint64_t end_timestamp;
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uint64_t start_ts_offest_ms;
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uint64_t end_ts_offset_ms;
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};
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// Taken from https://github.com/ggerganov/whisper.cpp/blob/master/examples/stream/stream.cpp
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std::string to_timestamp(uint64_t t)
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{
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uint64_t sec = t / 1000;
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uint64_t msec = t - sec * 1000;
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uint64_t min = sec / 60;
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sec = sec - min * 60;
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char buf[32];
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snprintf(buf, sizeof(buf), "%02d:%02d.%03d", (int)min, (int)sec, (int)msec);
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return std::string(buf);
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}
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struct whisper_context *init_whisper_context(const std::string &model_path_in,
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struct transcription_filter_data *gf)
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{
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@ -314,8 +300,8 @@ void run_inference_and_callbacks(transcription_filter_data *gf, uint64_t start_o
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vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_vad_state)
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{
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uint32_t num_frames_from_infos = 0;
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uint64_t start_timestamp = 0;
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uint64_t end_timestamp = 0;
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uint64_t start_timestamp_offset_ns = 0;
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uint64_t end_timestamp_offset_ns = 0;
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size_t overlap_size = 0;
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for (size_t c = 0; c < gf->channels; c++) {
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@ -342,8 +328,8 @@ vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_v
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while (gf->info_buffer.size >= size_of_audio_info) {
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circlebuf_pop_front(&gf->info_buffer, &info_from_buf, size_of_audio_info);
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num_frames_from_infos += info_from_buf.frames;
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if (start_timestamp == 0) {
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start_timestamp = info_from_buf.timestamp;
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if (start_timestamp_offset_ns == 0) {
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start_timestamp_offset_ns = info_from_buf.timestamp_offset_ns;
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}
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// Check if we're within the needed segment length
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if (num_frames_from_infos > max_num_frames) {
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@ -354,7 +340,7 @@ vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_v
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break;
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}
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}
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end_timestamp = info_from_buf.timestamp;
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end_timestamp_offset_ns = info_from_buf.timestamp_offset_ns;
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/* Pop from input circlebuf */
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for (size_t c = 0; c < gf->channels; c++) {
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@ -386,10 +372,10 @@ vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_v
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resampled_16khz[0] + resampled_16khz_frames);
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gf->vad->process(vad_input, false);
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const uint64_t start_offset_ms = start_timestamp / 1000000 - gf->start_timestamp_ms;
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const uint64_t end_offset_ms = end_timestamp / 1000000 - gf->start_timestamp_ms;
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const uint64_t start_ts_offset_ms = start_timestamp_offset_ns / 1000000;
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const uint64_t end_ts_offset_ms = end_timestamp_offset_ns / 1000000;
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vad_state current_vad_state = {false, start_offset_ms, end_offset_ms};
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vad_state current_vad_state = {false, start_ts_offset_ms, end_ts_offset_ms};
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std::vector<timestamp_t> stamps = gf->vad->get_speech_timestamps();
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if (stamps.size() == 0) {
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@ -397,8 +383,9 @@ vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_v
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resampled_16khz_frames);
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if (last_vad_state.vad_on) {
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obs_log(gf->log_level, "Last VAD was ON: segment end -> send to inference");
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run_inference_and_callbacks(gf, last_vad_state.start_timestamp,
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last_vad_state.end_timestamp, VAD_STATE_WAS_ON);
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run_inference_and_callbacks(gf, last_vad_state.start_ts_offest_ms,
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last_vad_state.end_ts_offset_ms,
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VAD_STATE_WAS_ON);
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}
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if (gf->enable_audio_chunks_callback) {
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@ -406,8 +393,8 @@ vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_v
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VAD_STATE_IS_OFF,
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{DETECTION_RESULT_SILENCE,
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"[silence]",
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current_vad_state.start_timestamp,
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current_vad_state.end_timestamp,
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current_vad_state.start_ts_offest_ms,
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current_vad_state.end_ts_offset_ms,
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{}});
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}
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} else {
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@ -447,29 +434,30 @@ vad_state vad_based_segmentation(transcription_filter_data *gf, vad_state last_v
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obs_log(gf->log_level, "VAD segment end -> send to inference");
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// find the end timestamp of the segment
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const uint64_t segment_end_ts =
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start_offset_ms + end_frame * 1000 / WHISPER_SAMPLE_RATE;
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run_inference_and_callbacks(gf, last_vad_state.start_timestamp,
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start_ts_offset_ms + end_frame * 1000 / WHISPER_SAMPLE_RATE;
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run_inference_and_callbacks(gf, last_vad_state.start_ts_offest_ms,
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segment_end_ts,
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last_vad_state.vad_on
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? VAD_STATE_WAS_ON
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: VAD_STATE_WAS_OFF);
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current_vad_state.vad_on = false;
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current_vad_state.start_timestamp = current_vad_state.end_timestamp;
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current_vad_state.end_timestamp = 0;
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current_vad_state.start_ts_offest_ms =
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current_vad_state.end_ts_offset_ms;
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current_vad_state.end_ts_offset_ms = 0;
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} else {
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current_vad_state.vad_on = true;
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if (last_vad_state.vad_on) {
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current_vad_state.start_timestamp =
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last_vad_state.start_timestamp;
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current_vad_state.start_ts_offest_ms =
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last_vad_state.start_ts_offest_ms;
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} else {
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current_vad_state.start_timestamp =
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start_offset_ms +
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current_vad_state.start_ts_offest_ms =
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start_ts_offset_ms +
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start_frame * 1000 / WHISPER_SAMPLE_RATE;
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}
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obs_log(gf->log_level,
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"end not reached. vad state: start ts: %llu, end ts: %llu",
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current_vad_state.start_timestamp,
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current_vad_state.end_timestamp);
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current_vad_state.start_ts_offest_ms,
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current_vad_state.end_ts_offset_ms);
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}
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last_vad_state = current_vad_state;
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}
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@ -152,3 +152,16 @@ std::vector<whisper_token_data> reconstructSentence(const std::vector<whisper_to
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return reconstructed;
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}
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std::string to_timestamp(uint64_t t_ms_offset)
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{
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uint64_t sec = t_ms_offset / 1000;
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uint64_t msec = t_ms_offset - sec * 1000;
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uint64_t min = sec / 60;
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sec = sec - min * 60;
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char buf[32];
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snprintf(buf, sizeof(buf), "%02d:%02d.%03d", (int)min, (int)sec, (int)msec);
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return std::string(buf);
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}
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@ -14,4 +14,12 @@ std::pair<int, int> findStartOfOverlap(const std::vector<whisper_token_data> &se
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std::vector<whisper_token_data> reconstructSentence(const std::vector<whisper_token_data> &seq1,
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const std::vector<whisper_token_data> &seq2);
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/**
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* @brief Convert a timestamp in milliseconds to a string in the format "MM:SS.sss" .
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* Taken from https://github.com/ggerganov/whisper.cpp/blob/master/examples/stream/stream.cpp
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* @param t_ms_offset Timestamp in milliseconds (offset from the beginning of the stream)
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* @return std::string Timestamp in the format "MM:SS.sss"
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*/
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std::string to_timestamp(uint64_t t_ms_offset);
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#endif /* WHISPER_UTILS_H */
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