Automatic Speech Recognition
NeMo
Finnish
asr
speech-recognition
canary-v2
kenlm
finnish
Eval Results (legacy)
Instructions to use RASMUS/Finnish-ASR-Canary-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use RASMUS/Finnish-ASR-Canary-v2 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("RASMUS/Finnish-ASR-Canary-v2") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
File size: 5,719 Bytes
cde7fe4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 | #include "decoder_utils.h"
#include <algorithm>
#include <cmath>
#include <limits>
std::vector<std::pair<size_t, float>> get_pruned_log_probs(
const std::vector<double> &prob_step,
double cutoff_prob,
size_t cutoff_top_n) {
std::vector<std::pair<int, double>> prob_idx;
for (size_t i = 0; i < prob_step.size(); ++i) {
prob_idx.push_back(std::pair<int, double>(i, prob_step[i]));
}
// pruning of vacobulary
size_t cutoff_len = prob_step.size();
if (cutoff_prob < 1.0 || cutoff_top_n < cutoff_len) {
std::sort(
prob_idx.begin(), prob_idx.end(), pair_comp_second_rev<int, double>);
if (cutoff_prob < 1.0) {
double cum_prob = 0.0;
cutoff_len = 0;
for (size_t i = 0; i < prob_idx.size(); ++i) {
cum_prob += prob_idx[i].second;
cutoff_len += 1;
if (cum_prob >= cutoff_prob || cutoff_len >= cutoff_top_n) break;
}
}
prob_idx = std::vector<std::pair<int, double>>(
prob_idx.begin(), prob_idx.begin() + cutoff_len);
}
std::vector<std::pair<size_t, float>> log_prob_idx;
for (size_t i = 0; i < cutoff_len; ++i) {
log_prob_idx.push_back(std::pair<int, float>(
prob_idx[i].first, log(prob_idx[i].second + NUM_FLT_MIN)));
}
return log_prob_idx;
}
std::vector<std::pair<double, std::string>> get_beam_search_result(
const std::vector<PathTrie *> &prefixes,
const std::vector<std::string> &vocabulary,
size_t beam_size,
std::vector<std::tuple<std::string, uint32_t, uint32_t>>& wordlist) {
// allow for the post processing
std::vector<PathTrie *> space_prefixes;
if (space_prefixes.empty()) {
for (size_t i = 0; i < beam_size && i < prefixes.size(); ++i) {
space_prefixes.push_back(prefixes[i]);
}
}
std::sort(space_prefixes.begin(), space_prefixes.end(), prefix_compare);
std::vector<std::pair<double, std::string>> output_vecs;
std::vector<uint32_t> timestamps;
for (size_t i = 0; i < beam_size && i < space_prefixes.size(); ++i) {
std::vector<int> output;
// request timestamp only for best result
space_prefixes[i]->get_path_vec(output, i == 0 ? ×tamps : nullptr);
// convert index to string
std::string output_str;
for (size_t j = 0; j < output.size(); j++) {
output_str += vocabulary[output[j]];
}
std::pair<double, std::string> output_pair(space_prefixes[i]->score,
output_str);
output_vecs.emplace_back(output_pair);
}
// update word list with word and corresponding start & end times
wordlist.clear();
if (output_vecs[0].second.size() > 0) {
int ts_idx = 0;
char* saveptr;
char transcript[output_vecs[0].second.size() + 1];
strcpy(transcript, output_vecs[0].second.c_str());
char* token = strtok_r(transcript, " ", &saveptr);
while (token != NULL) {
std::tuple<std::string, uint32_t, uint32_t> word(std::string(token), timestamps[ts_idx], timestamps[ts_idx + 1]);
wordlist.emplace_back(word);
token = strtok_r(NULL, " ", &saveptr);
ts_idx += 2;
}
}
return output_vecs;
}
size_t get_utf8_str_len(const std::string &str) {
size_t str_len = 0;
for (char c : str) {
str_len += ((c & 0xc0) != 0x80);
}
return str_len;
}
std::vector<std::string> split_utf8_str(const std::string &str) {
std::vector<std::string> result;
std::string out_str;
for (char c : str) {
if ((c & 0xc0) != 0x80) // new UTF-8 character
{
if (!out_str.empty()) {
result.push_back(out_str);
out_str.clear();
}
}
out_str.append(1, c);
}
result.push_back(out_str);
return result;
}
std::vector<std::string> split_str(const std::string &s,
const std::string &delim) {
std::vector<std::string> result;
std::size_t start = 0, delim_len = delim.size();
while (true) {
std::size_t end = s.find(delim, start);
if (end == std::string::npos) {
if (start < s.size()) {
result.push_back(s.substr(start));
}
break;
}
if (end > start) {
result.push_back(s.substr(start, end - start));
}
start = end + delim_len;
}
return result;
}
bool prefix_compare(const PathTrie *x, const PathTrie *y) {
if (x->score == y->score) {
if (x->character == y->character) {
return false;
} else {
return (x->character < y->character);
}
} else {
return x->score > y->score;
}
}
void add_word_to_fst(const std::vector<int> &word,
fst::StdVectorFst *dictionary) {
if (dictionary->NumStates() == 0) {
fst::StdVectorFst::StateId start = dictionary->AddState();
assert(start == 0);
dictionary->SetStart(start);
}
fst::StdVectorFst::StateId src = dictionary->Start();
fst::StdVectorFst::StateId dst;
for (auto c : word) {
dst = dictionary->AddState();
dictionary->AddArc(src, fst::StdArc(c, c, 0, dst));
src = dst;
}
dictionary->SetFinal(dst, fst::StdArc::Weight::One());
}
bool add_word_to_dictionary(
const std::string &word,
const std::unordered_map<std::string, int> &char_map,
bool add_space,
int SPACE_ID,
fst::StdVectorFst *dictionary) {
auto characters = split_utf8_str(word);
std::vector<int> int_word;
for (auto &c : characters) {
if (c == " ") {
int_word.push_back(SPACE_ID);
} else {
auto int_c = char_map.find(c);
if (int_c != char_map.end()) {
int_word.push_back(int_c->second);
} else {
return false; // return without adding
}
}
}
if (add_space) {
int_word.push_back(SPACE_ID);
}
add_word_to_fst(int_word, dictionary);
return true; // return with successful adding
}
|